Nobody is pitching Web3 at dinner parties anymore. The term itself has aged out of the vocabulary that founders reach for when they want to sound current, replaced almost entirely by whatever the latest AI agent framework happens to be called that week. And yet, away from the panels and the headline cycle, a narrower and less flashy version of the Web3 thesis is finding real money again — not tokens, not NFTs, but the unglamorous plumbing underneath them.

That is the argument Varun Datta, CEO of the London-based global Web3 venture capital firm Truth Ventures, laid out recently in an op-ed for London Loves Business. Datta’s case is deliberately unfashionable: Web3 was never really about speculation, he argues; it was about infrastructure that took a decade to mature enough for anyone outside crypto Twitter to take seriously. The businesses he backs — Bittensor, StarkNet, peaq, Ternoa, 1inch — do not chase narratives. They solve scaling, coordination, and liquidity problems that decentralised systems have carried since the Ethereum ICO era.

What makes the timing interesting is that Datta is not alone, and he is not describing a niche. Galaxy Research data cited by Waveup puts 2025 crypto and blockchain venture investment above $20 billion across roughly 1,660 deals — more than double 2023’s total, and the strongest year since the 2022 peak. The composition of that money has changed just as much as its size. The bulk of it went to later-stage rounds, the largest late-stage share the sector has recorded, while pre-seed held at roughly a quarter of the deal count. Investors are not funding whitepapers. They are funding companies with usage numbers to defend.

The institutions showed up quietly, then all at once

Datta’s stronger point is not about crypto-native funds at all — it is about who else has started paying attention. He traces a shift among traditional finance players from merely holding digital assets to actually engaging with the infrastructure beneath them. The Economist has written publicly about the efficiencies tokenisation could unlock in settlement systems. BNP Paribas has explored public blockchain rails for money market fund tokenisation. And Intercontinental Exchange, the parent of the New York Stock Exchange, has confirmed talks with Hyperliquid — with ICE’s own CEO reportedly describing the decentralised trading platform as bigger than Nasdaq.

“I genuinely feel there has been a real change in sentiment, interest and imminent investment,” Datta writes, describing the shift among institutions once confined to volatility warnings and regulatory caution.

That framing matters for how this story gets told next. For years, Web3 coverage defaulted to a binary — either the technology was a bubble, or it was inevitable. Datta’s argument, and the capital flows behind it, suggest something less dramatic and more durable: infrastructure businesses building unglamorous, necessary layers — coordination, execution, privacy, liquidity — while speculative attention moved elsewhere. It is the same pattern the early internet went through, when the companies that mattered most in hindsight were rarely the ones consumers interacted with directly. PayPal and Stripe built payment rails. AWS built cloud infrastructure. Nobody was writing hot takes about either at the time.

India’s problem isn’t talent. It’s the tax code

Set this global re-rating against India, and the contrast gets uncomfortable fast. The country has one of the largest developer populations working on blockchain tooling anywhere, and by industry estimates cited by MEXC’s 2026 market guide, more than 150 million Indians hold or have held crypto assets — reportedly the largest user base of any country. None of that has translated into India becoming a serious base for Web3 infrastructure capital, and the policy explains why.

The Union Budget for 2026–27 confirmed, once again, that the 30% flat tax on crypto gains and the 1% TDS on transactions will remain untouched, alongside tighter penalties for reporting failures. Industry bodies like the Bharat Web3 Association have argued the framework pushes trading activity and, increasingly, company registration offshore. The government’s counter-argument is fiscal discipline and consumer protection, and it is not wrong on either count — but the effect on infrastructure founders, who need liquid token markets and predictable compliance far more than retail traders do, has been to make India a place to build from rather than a place to base a company.

There is a second, quieter track running alongside the punitive one. MeitY’s Blockchain India Challenge, launched this year, is actively funding startups building blockchain tooling for governance and public-sector use — tamper-proof land records, supply chain verification, that kind of infrastructure. It is a genuine signal that the state distinguishes between “crypto as speculation” and “blockchain as infrastructure,” which is precisely the distinction Datta’s op-ed is trying to draw for a global VC audience. India has simply drawn that line inside government procurement rather than private capital markets, which limits how much of the current infrastructure investment cycle the country can actually capture.

The Gulf built the opposite trade

MENA, and the UAE specifically, has spent the same three years doing the reverse: trading regulatory ambiguity for regulatory density, on the bet that clarity itself is the product institutional infrastructure capital is shopping for. Dubai’s Virtual Assets Regulatory Authority has spent 2026 tightening rather than loosening its rulebook, fully implementing Travel Rule requirements for licensed virtual asset service providers as of February. Abu Dhabi Global Market, running under the common-law framework familiar to institutional lawyers in London and New York, has become the preferred venue for custody and tokenisation businesses that need a jurisdiction with case law rather than experimental policy.

The volume of activity is no longer boutique. The Dubai Multi Commodities Centre alone has crossed 2,500 registered blockchain and crypto entities, and custody bank BNY has partnered with Finstreet and the ADI Foundation to bring bitcoin and ether custody infrastructure into ADGM — the kind of institutional plumbing that only gets built where the regulator has already answered the questions a compliance officer would ask first. None of this reads as speculative enthusiasm. It reads as a jurisdiction methodically building exactly the infrastructure layer Datta’s thesis says the next cycle of Web3 value will accrue to.

The gap that matters is regulatory, not technological

Strip away the geography and Datta’s underlying question is a useful filter for any infrastructure bet, Web3 or otherwise: does the technology solve a problem that persists regardless of market conditions, and would users keep relying on it if speculative interest disappeared tomorrow? Bittensor’s wager on decentralised compute coordination, StarkNet’s bet on execution speed, peaq’s push into machine-owned digital identity — none of these depend on a bull market to matter. They depend on enough builders choosing to build there.

Where those builders choose to base themselves is now visibly a function of policy, not proximity to talent. India has the engineers. It does not yet have the tax and compliance environment that lets an infrastructure company incorporate, raise, and pay contributors in tokens without a 30% penalty attached to nearly every step. The Gulf has built that environment deliberately and is now absorbing capital and company formation that could just as easily have gone to Bengaluru or Gurugram. If Web3 infrastructure really is entering the phase Datta describes — quieter, more institutional, less dependent on headlines — then the jurisdictions that win this decade will be the ones that decided early which side of the “speculation versus infrastructure” line they wanted to regulate for. India has made that distinction inside government contracts. The Gulf has made it inside its entire regulatory architecture. That difference, more than any single funding round, is what will decide where the next Bittensor gets built.

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Cradlewise has raised $12 million in a Series A led by 3one4 Capital and Prudent Investment Management, bringing total funding to $26 million alongside earlier backers Sean O’Sullivan Ventures, Footwork VC, and Charles River Ventures. The company’s previous round, a $7 million raise, closed in November 2021 — nearly five years before this one.

Radhika Patil and Bharath Patil, a husband-and-wife team with master’s degrees in electronics from the Indian Institute of Science, founded the company in 2019. Radhika, chief executive, previously worked on power management systems for Qualcomm’s Snapdragon processors; both have engineering backgrounds spanning Qualcomm and Texas Instruments. Their product is a convertible smart crib: sensors track a baby’s movement, sound, and sleep state, and the system predicts an impending wake-up and begins rocking pre-emptively to resettle the child before they fully wake. A contactless, night-vision monitor is built in, removing the need for a separate camera. The crib converts from a bassinet to a full crib and is designed to last until a child is about two, retails at roughly $1,799, and won a TIME Best Inventions award in 2020. Cradlewise says its prediction models are trained on more than 75 million hours of sleep data and that the product saves parents up to two hours of effort a day.

Where most smart sleep hardware simply responds to crying, Cradlewise is trying to intervene before a baby is fully awake — a harder sensing problem, and the reason the company’s training-data claim matters more than it might elsewhere. The convertibility is the sharper commercial argument, though. Rival Happiest Baby’s SNOO is a bassinet covering roughly the first six months, after which families buy a separate crib. Cradlewise, at a comparable $1,799 against SNOO’s $1,695, covers around two years on a single purchase — a useful life four times longer for a near-identical price, in a category where the standing objection is that this is a lot of money for nursery furniture.

Also read: Mokobara Raises ₹170 Crore, but Filings Show Just ₹91 Crore of New Shares

Manufacturing runs out of an integrated facility in Pune capable of producing, testing and packing thousands of cribs a month, with the company operating from California and Bengaluru and selling almost entirely into the United States since 2021. Owning that line, rather than contracting to China as most consumer hardware companies do at this scale, gives Cradlewise the ability to iterate on the product without renegotiating with a factory — a capability that takes years to build and that a Series A alone could not buy.

It also leaves the company exposed on two fronts the funding announcement does not address. SNOO holds FDA authorisation as a medical device for keeping infants safely positioned during sleep; Cradlewise has no equivalent clearance, which matters in a category where the underlying buyer anxiety is safety rather than convenience. And a Pune-manufactured, America-sold $1,799 device has limited room to absorb import duty before either margin or price has to move — an arrangement that made sense when Indian goods entered the US cheaply, and carries different risk now. Neither issue is named among the round’s four stated uses: growth, channel expansion, product research and geographic expansion.

The nearly five-year gap since Cradlewise’s last raise, and the Series A label attached to a round that follows $14 million already invested, suggests the company grew carefully through a market that stayed closed to it for a long stretch — a modest total of $26 million for a seven-year-old hardware company selling a premium product in America.

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Bengaluru-based Mokobara has raised ₹170 crore, about $18 million, in a Series C round led by Sauce.vc, with Peak XV Partners, AYRA Ventures, Niveshaay Investment, and existing backers taking part. The company has issued no formal statement, and the regulatory paper trail tells a smaller story than the headline number.

The board has approved 1,300 Series C compulsorily convertible preference shares at ₹6.2 lakh apiece — ₹80 crore — plus a further 199 shares at ₹5.4 lakh each, adding ₹10.7 crore. That totals ₹90.66 crore of new issuance against a ₹170 crore round. Sauce.vc vice president Karan Kathpalia has separately said the firm alone put in ₹109 crore, a figure that on its own exceeds the entire approved allotment. The gap points to secondary activity: existing shareholders selling stock to Sauce.vc and other investors rather than the company issuing new shares against all of the headline sum. If that reading holds, Mokobara receives roughly ₹91 crore in the business, and early backers cash out close to ₹79 crore at a valuation nearly three times higher than their entry price — a good outcome for everyone involved, just a different transaction than the one being announced.

Reported figures put the post-money valuation at around ₹1,930 crore, roughly $203 million, up from ₹700 crore at the Series B in February 2024. After allotment, Sauce.vc holds 20.48 percent, Peak XV 16.76 percent, and Saama Capital 13.65 percent. Co-founders Sangeet Agrawal and Navin Parwal hold 21.46 percent and 11.25 percent, respectively, together retaining close to a third of the company at Series C — a healthy position at this stage, though the gap between the two founders’ stakes is unusual and remains unexplained.

Agrawal and Parwal met while working at the furniture brand Urban Ladder, where they watched design turn a commodity category into one buyers would pay a premium for. They spent eighteen months building a first product and were turned down by 33 investors before Sauce.vc’s Manu Chandra wrote the opening cheque. Mokobara now sells luggage, backpacks, totes, slings, wallets and travel accessories online and through roughly 50 stores across Bengaluru, Delhi, Mumbai and Pune, plus one in Dubai opened in February 2025.

The underlying business has grown fast enough to justify scrutiny rather than dismiss it. Operating revenue nearly doubled to ₹230.15 crore in FY25 from ₹117.44 crore, itself more than double the ₹53 crore booked the year before. Net loss widened to ₹10.18 crore from ₹4.24 crore — about 4.4 percent of revenue, a lean ratio for a D2C brand mid-expansion. Against FY25 revenue, the reported ₹1,930 crore valuation works out to roughly eight times sales, defensible for a company that has doubled revenue twice, though it also assumes FY26 continues the pattern, and FY26 numbers are not yet out.

Luggage carries structural advantages few Indian D2C categories share: high average order value, a limited SKU count, no expiry, and a considered purchase customers want to physically handle before buying — the wheels, the handle, the weight. A store selling ₹10,000 suitcases can cover its lease on modest footfall, unlike categories with thin tickets and shelf-space fees. The 50-store network is the part of Mokobara’s story still untested: fifty locations is the point at which a brand stops being capital-light, and store-level unit economics have not been disclosed.

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Growth gets a lot of attention. Bigger revenue. Bigger teams. Bigger office. Bigger customer numbers. But none of those things automatically make a business stronger. Over the last few years, plenty of companies have learned this the hard way. Demand went up, sales looked great on paper, but operations couldn’t keep up. Deliveries slowed down. Customer support became overloaded. Costs climbed faster than revenue. That’s growth. Scaling is something different. It means building a business that can handle more customers without creating twice the amount of work every time sales increase. And honestly, that’s where the real competitive advantage usually comes from.

Growth Is Exciting, Scaling Is Sustainable

Adding customers isn’t the difficult part anymore. Keeping service levels consistent while those customers keep coming in — that’s where businesses either become stronger or start falling apart.

Growing often means hiring more people, renting more warehouse space, buying more inventory and increasing expenses across the board. Revenue increases, but so do operating costs. Scaling looks at the same problem from another angle. Instead of constantly adding resources, businesses improve the way work gets done. Better systems. Clearer processes. Smarter planning. A little automation where it actually makes sense.

The goal isn’t to work harder. It’s to stop creating unnecessary work in the first place.

The stakes here are backed by hard survival numbers. U.S. Bureau of Labor Statistics data tracking business establishments over multiple decades shows that only about half of new businesses make it past their fifth year, and the ones that do typically survive because employment and operations grew in a controlled, structured way rather than in a sudden scramble to meet demand. Scaling, in other words, isn’t just a nice-to-have efficiency exercise — it’s closely tied to whether a business is still around in five years.

Systems Usually Beat Effort

One mistake growing companies make is depending too much on people fixing problems every day. That works for a while. Eventually someone takes leave, demand suddenly spikes, or a key employee resigns. Then everything starts slowing down because too much knowledge existed inside people’s heads instead of inside documented processes.

Businesses that scale well usually have a different mind-set. They create repeatable systems. That could mean:

• Automated order processing
• Inventory that’s updated in real time
• Clear approval workflows
• Standard operating procedures
• Dashboards instead of endless spreadsheets

Together, all of these things remove a surprising amount of daily friction.

Infrastructure Matters More Than People Think

Technology usually gets all the headlines. AI. Automation. Analytics. Those are important. But physical operations still matter just as much, especially for businesses that manufacture, distribute or ship products every day.

As order volumes increase, even small inefficiencies become expensive. A warehouse layout that worked perfectly six months ago suddenly creates delays. Packaging slows everything down. Products get damaged more often. Teams spend more time moving inventory than actually fulfilling orders.

That’s why growing businesses eventually start standardising the basics. Packaging methods become consistent. Storage systems become more organised. Equipment gets upgraded. For many logistics businesses, that also includes switching to durable handling equipment like plastic pallets, alongside reusable containers and better warehouse layouts that reduce unnecessary handling throughout the supply chain. Nobody builds an entire growth strategy around pallets. But lots of businesses quietly improve efficiency by fixing these smaller operational details.

The importance of these unglamorous fixes shows up at a national level too. The World Bank’s Logistics Performance Index benchmarks countries on exactly these factors — infrastructure quality, shipment reliability, and the efficiency of moving goods — and consistently finds that companies operating in lower-scoring markets face real cost and delay penalties regardless of how strong their sales numbers look. Warehouse layout and handling equipment aren’t side issues; they’re part of the same infrastructure question governments and economists take seriously at scale.

Technology Isn’t the Answer to Everything

There’s been plenty of discussion around artificial intelligence over the last year. It can absolutely improve operations. Predict demand. Automate repetitive work. Improve forecasting. Speed up reporting. But technology doesn’t magically solve broken processes.

If an inefficient workflow gets automated, it usually just becomes an inefficient workflow running faster. The companies getting the biggest value from AI are usually the ones that already have clean data, consistent processes and clear operational goals. Because in the end, technology works best when it’s supporting a good system instead of replacing one.

This gap between adoption and impact shows up in the data too. According to Stanford University’s AI Index Report, a large majority of organizations have already adopted AI in at least one business function, yet only a small fraction have managed to scale it into full production use. The technology itself isn’t usually the obstacle — the missing piece is almost always the underlying process it’s meant to support.

Scaling Starts with Asking Better Questions

Before expanding, smart businesses usually step back and ask a few practical questions.

• Can current systems handle twice the workload?
• Will customers still receive the same level of service?
• Can new employees become productive quickly?
• Will suppliers keep up if demand suddenly increases?
• Can inventory be tracked accurately from purchase to delivery?

These questions are often the difference between sustainable growth and expensive chaos.

Efficiency Has Become a Competitive Advantage

The business environment isn’t getting simpler. Supply chains remain unpredictable. Customer expectations continue rising. Every year, the competition picks up speed. Businesses that maintain their competitiveness aren’t always the biggest and powerful ones. But because their operations aren’t under continual strain, they are frequently the companies that react more quickly.

Strong systems make decisions quicker. Clear processes reduce mistakes. Reliable infrastructure creates consistency. That combination is much harder for competitors to copy than a marketing campaign or a new product launch.

Final Thoughts

Fast growth looks impressive. Scalable operations last longer. When demand rises, companies that make investments in improved workflows, robust infrastructure, intelligent technology, and repeatable procedures typically find themselves in a much stronger and better position.

Opportunities come with growth. Scaling makes sure the business is actually ready for it.

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Start-ups don’t usually begin with a hiring strategy. They begin with urgency. Someone leaves, a new client comes in, funding lands, and suddenly another pair of hands is needed. A founder reaches out to a former colleague. An employee recommends a friend. A LinkedIn post goes live. A few conversations later, there’s a new hire. And honestly, that’s not a bad way to start.

When there are eight or ten people in the company, everyone knows what’s going on anyway. People jump between tasks, help each other out, and nobody is too worried about job titles. The trouble starts when the business keeps growing, but the hiring process doesn’t. It happens quietly. One day there are 15 people. Then 40. Then 80. Suddenly, the same approach that once helped the company move fast starts creating problems nobody planned for.

When Everyone Does Everything

Almost every startup goes through this phase. Marketing helps with sales. Sales jumps into customer support. Operations somehow ends up handling HR because there’s nobody else to do it. It actually feels exciting. People like wearing different hats because they’re building something together. But eventually those hats become a problem.

Two employees are doing almost identical work but have different titles. A new hire negotiates a higher salary than someone who’s been there for years. Managers have different expectations for the same position because nobody ever stopped to define what the role actually involves. None of this happens because anyone made a bad decision. It happens because the company grew faster than its internal structure.

This kind of drift carries more than an internal fairness problem. The U.S. Equal Employment Opportunity Commission makes clear that pay equity is assessed by what a job actually involves, not by the title attached to it — meaning inconsistent titles and undefined roles can turn into real legal exposure once a company is large enough to be scrutinised, not just an awkward internal conversation.

Hiring Gets Harder Than It Looks

Growing a team isn’t just about filling empty seats. The bigger challenge is hiring the right person for the stage the company is in. Early on, generalists are incredibly valuable. They’re comfortable figuring things out as they go and don’t mind stepping outside their job description. Later, that’s not always enough. A company that wants to scale its marketing probably needs someone who understands performance marketing inside out. The finance team needs people who can handle forecasting and compliance. Sales starts looking for specialists instead of people who simply “know how to sell.” Those are very different conversations from the ones founders were having a year earlier.

Founders Eventually Become the Bottleneck

This catches almost every growing company. The founders are still reading every CV. They’re still sitting in every final interview. They’re still approving every offer. It feels like quality control. In reality, it slows everything down.

Good candidates don’t wait forever. If another company makes a decision first, they’re gone. Meanwhile, department heads are left waiting because nobody wants to make a hiring decision without founder approval. At some point, the business has to trust its managers to hire well. That only works if everyone is hiring against the same standards instead of personal opinions.

The cost of that hesitation is measurable. The Society for Human Resource Management has found that it takes companies over a month on average to fill an open role, and every extra day a founder sits on an approval adds to that timeline. When hiring decisions bottleneck at the top, the delay isn’t just an inconvenience — it’s added directly to the cost of every open seat.

Growth Needs More Than Good Instincts

Instinct is great. It’s one of the reasons start-ups move so quickly in the first place. But instinct becomes harder to scale. A team of ten can rely on conversations. A team of one hundred can’t. People want to know what’s expected from their role. Managers want a clear way to measure performance. Employees want promotions to feel fair instead of random. That’s usually when businesses begin putting more structure around their people processes. Many introduce frameworks like job evaluation to make sure responsibilities are clearly defined, and similar roles are treated consistently as the organisation grows.

It’s not about adding unnecessary rules. It’s about removing uncertainty.

Also read: Why Choosing Global HR Services is Crucial for International Success

The Boring Stuff Starts Becoming Important

Nobody launches a start-up dreaming about payroll software or HR systems. Founders think about customers, products, investment, and growth. The operational side comes later. But later always arrives. Simple things suddenly matter a lot. Documented processes. Clear reporting lines. Performance reviews that aren’t based on memory. A system for onboarding new employees so every manager isn’t reinventing the process. They’re the reason many growing companies become easier to manage instead of more chaotic.

Structure earns its keep here in ways that are easy to underestimate. Gallup’s research has found that only about one in eight employees strongly agree their company does a great job onboarding new hires, and weak onboarding is directly linked to employees leaving within their first year and a half. A documented process doesn’t just save a manager’s time once a company scales past a handful of people — it’s often the difference between a new hire staying or quietly heading for the door.

According to the World Economic Forum, businesses across industries are placing greater emphasis on workforce planning and future skills as technology continues reshaping jobs. That’s no longer something only enterprise companies think about. Start-ups are dealing with the same reality much earlier in their journey.

LinkedIn’s Economic Graph has also reported a growing shift toward skills-first hiring, showing that companies are paying closer attention to what people can actually do rather than relying only on traditional qualifications.

Scaling Is Really About Building Better Systems

Fast-growing start-ups often think growth is about hiring more people. It isn’t. Hiring is only one piece of it. The harder part is building a company where every new employee understands their role, managers make consistent decisions, and teams don’t lose speed simply because the business became larger. That’s usually the point where founders realise the first hiring strategy did exactly what it was supposed to do. It got the company started. Getting to the next stage takes something different.

The post When Start-up Hiring Stops Scaling: Building HR Structure Before It’s Forced On You appeared first on LAFFAZ.

Sugar Cosmetics has raised ₹144.5 crore entirely from existing investor A91 Partners, which subscribed to the whole issue. The board approved allotment of 1,12,248 Series D7 compulsorily convertible preference shares at ₹12,871 each to A91 Emerging Fund III on 1 September, taking the firm’s stake to roughly 19.97 percent. No new investor took part.

Estimates of the post-money valuation range between ₹550 crore and ₹755 crore — 75 to 82 percent below the roughly ₹3,000 crore Sugar carried in 2022, when L Catterton led a $50 million Series D. The figure also sits well under the ₹1,400-1,500 crore the company was reportedly seeking as recently as mid-2026, itself already half its peak.

The business has now contracted for two straight years. Revenue fell about 20 percent to ₹404 crore in FY25 from ₹505 crore — the company’s first decline since founding — while net loss nearly doubled to ₹135 crore and EBITDA loss more than doubled to ₹116 crore. FY26 revenue has been reported at roughly ₹380 crore, lower again. Cumulative losses across five years now total close to ₹375 crore, and Sugar has not yet recorded a profitable year. A valuation report dated 30 June 2026, attached to the filing, states that the company has shown a sustained and worsening pattern of financial deterioration across the past two financial years — a formal assessment made under professional liability, not editorial characterisation, and evidently the backdrop against which A91 wrote its cheque.

The secondary market tells a consistent story. Stakes worth up to ₹150 crore are reportedly being shopped by early backers, with a consulting firm pitching Sugar shares at a fraction of peak valuation and a minimum ticket of around ₹25 crore — the kind of structured, discounted process that typically surfaces around distressed rather than healthy companies.

Vineeta Singh and Kaushik Mukherjee, IIM Ahmedabad alumni and a married couple, founded the Mumbai-based company in 2015; Singh is chief executive and Mukherjee chief operating officer. Sugar sells through its own platform, marketplaces, more than 200 exclusive outlets across 50 cities and roughly 50,000 retail touchpoints — the very network that now sits at the centre of its cost problem. The 2022 round funded an aggressive push into physical retail, a defensible strategy for a colour cosmetics brand where shoppers want to swatch a shade before buying. But leases, store staff, and distributor commitments are fixed costs, locked in for years, and none of them fell when revenue did. Sugar has reportedly since closed 30 to 40 percent of the stores it opened because per-store economics stopped working, and a closed store does not release its lease immediately.

What Sugar has that a fresh cheque cannot buy is a decade of brand equity, distribution across 550 cities a new entrant cannot replicate quickly, and formulations built for Indian skin tones and climate. What ₹144.5 crore against ₹135 crore of annual losses buys is roughly a year to prove the business can be sold at a positive margin rather than simply sold at scale — a materially different task from the growth story the company was telling in 2022.

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Bengaluru-based Pixxel has closed a $100 million Series C co-led by Temasek and Seraphim Space, marking the largest single funding round any Indian spacetech company has raised. New investors 360 ONE Asset and IMM Investment joined existing backers Radical Ventures and growX Ventures in the round, which takes Pixxel’s total funding to $195 million at a reported valuation between $450 million and $500 million.

The fresh capital pushes Pixxel beyond its hyperspectral imaging roots into a wider build-out: advanced sensing satellites, high-resolution optical imaging spacecraft, an expanded Honeybee constellation, a scaled-up Aurora Earth intelligence platform, additional capacity at its Gigapixxel manufacturing facility, and sovereign space systems work.

Awais Ahmed and Kshitij Khandelwal started the company in February 2019 as undergraduates at BITS Pilani, bootstrapping the earliest prototypes with money borrowed from Ahmed’s father. Seven years on, Pixxel operates six Firefly satellites launched through 2025 that image at 5-metre resolution across more than 150 spectral bands with a 40-kilometre swath — spectral depth the company says no other commercial operator has matched. Where a conventional Earth observation satellite reads roughly eight colour bands, enough to confirm a field is green, Pixxel’s sensors read a material’s spectral signature, distinguishing a nitrogen-deficient patch of crop, a methane leak along a pipeline, or the mineral composition of a mine tailings pond, from orbit.

Also Read: Pixxel and Sarvam AI Will Put a Data Centre in Orbit by End of 2026

That capability underwrites a customer list few Indian deep-tech companies can claim. Pixxel holds a slot in NASA’s $476 million Commercial SmallSat Data Acquisition programme, running through November 2028, and in May signed a five-year agreement with the US National Reconnaissance Office to feed hyperspectral data into the agency’s remote sensing architecture. Domestically, it has won multiple Ministry of Defence iDEX challenges and was picked to lead India’s first public-private Earth observation constellation, a 12-satellite build under IN-SPACe.

The Indian entity’s financials sit well below the price tag. Operating revenue rose to ₹39.3 crore in FY25 from ₹30.6 crore a year earlier, while net loss widened to ₹30.8 crore from ₹20.4 crore. Pixxel has said a substantial share of group revenue is booked through overseas subsidiaries across the US, Europe, West Asia, Southeast Asia and Australia that these India filings do not capture — a claim consistent with where its largest government customers sit, though consolidated numbers remain unpublished. What is being priced, in effect, is the contracted pipeline: NASA through 2028, a five-year NRO agreement, iDEX awards and the IN-SPACe constellation, collateral that renews and expands the way commercial imagery contracts rarely do.

The structural detail investors are underwriting is the company’s dual-geography build. Pixxel’s parent is incorporated in Delaware and based in El Segundo, California, while the Bengaluru entity handles engineering and manufacturing — an architecture that lets a company founded in a college dorm hold a five-year US intelligence contract while simultaneously leading India’s sovereign Earth observation programme and winning Indian defence challenges. In-Q-Tel, the venture arm tied to the American intelligence community, sits on the cap table. It is an unusual position to occupy inside two governments’ supply chains at once, and it is a large part of what a sovereign fund like Temasek is betting on.

The optical-imaging push funded by this round is also a departure from Pixxel’s defensible niche. Planet, Maxar, BlackSky, and Satellogic already compete in that market, where pricing and revisit rate matter more than spectral depth. A company leaves a niche it built for seven years when it decides that niche cannot support the valuation it has just achieved.

The round follows Skyroot Aerospace crossing the $1 billion mark to become India’s first spacetech unicorn, adding to signs that Indian investors and sovereign funds are now willing to price space infrastructure companies years ahead of revenue that matches.

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Global appetite for physical silver has climbed sharply in recent years. The Silver Institute forecasts physical investment demand will rise 20% to 227 million ounces in 2026, a three-year high, as retail buyers return to bars and coins. As more first-time buyers enter the market, knowing what to check before paying becomes more important, not less.

Silver bars may look similar, yet their resale value depends on more than weight alone.

Before paying for silver bullion, a buyer should check the serial number, purity mark, refinery name, assay information, and storage conditions.

These details connect a specific product to its manufacturer and technical records. They also help dealers verify the bar faster when the owner decides to sell, transfer, insure, or redeem it.

Why a Serial Number Matters

Think of a serial number as a bar’s fingerprint — assigned to that one piece of metal alone, so it can never be confused with another bar of the same weight from the same refinery.

That number usually shows up in two places: stamped into the metal itself, and printed on the assay card. A match confirms the bar is exactly what its certificate claims. If the two numbers don’t line up, don’t take the seller’s word for it — get it checked before you pay.

This step is not just a formality: more than 1,000 counterfeit gold bars worth over $50 million surfaced in vaults worldwide in 2019. Silver carries the same exposure on a smaller scale, which is why matching a serial number against its certificate is so important.

Serial numbers also support ownership records in professional vaults. A provider can show which bar belongs to a client, where it is stored, and when it entered or left the facility.

Reputable platforms let buyers view their silver, vault location, and serial numbers through an online account or app. They keep silver products fully allocated and stored in DMCC-licensed vaults, with independent audits.

Why You Should Check on an Assay Record

An assay confirms the metal content and purity of a bullion product. Investment-grade silver bars commonly carry a fineness mark such as 999, which means the product contains 99.9% pure silver.

A complete assay record should match the physical bar. Buyers should compare every visible detail — weight, dimensions, refinery mark, and any assayer signature — before confirming an order or accepting delivery.

A certificate does not replace the bar itself, but it supports its identity and stated purity. Buyers who skip this comparison take on a risk that a few minutes of checking would otherwise remove.

Refinery Identification Supports Resale

Recognised refineries follow defined production and quality-control procedures. Their products are easier to identify because the weight, markings, dimensions, and packaging follow established specifications.

The refinery name should be clearly stamped on the bar and repeated on the assay card. Buyers should avoid products with unclear logos, spelling errors, altered surfaces, or incomplete manufacturer details.

Look for silver bars listed with 999 fineness, serial numbers, and assay records, sourced from accredited refineries and available in sizes from 10 grams to 1 kilogram.

Recognition affects liquidity. A well-documented bar from a known refinery usually requires fewer checks than an unbranded product with no supporting certificate.

How Professional Vault Storage Preserves Bullion Value

Silver doesn’t handle the outside world well. Left exposed, it reacts with oxygen and moisture in the air, tarnishing over time, and a scratched surface or torn assay packaging only adds to the damage — all of which chips away at what the bar is worth on resale.

A professional, climate-controlled vault sidesteps most of that damage by keeping temperature and humidity steady. There’s also a less obvious benefit: because the metal never leaves a secure, audited facility, it stays within what’s often called an unbroken chain of integrity, shielded from the wear and tear that ordinary storage can’t prevent.

When the owner decides to sell, silver held in such verified vaults can often be liquidated instantly at full market value without requiring expensive, time-consuming re-testing. That difference matters more as investment demand grows: rising retail buying of bars and coins has tightened physical liquidity in several markets over the past two years, making a documented, vault-stored bar easier to move quickly than an unverified one kept at home.

Keep Records Ready for Future Resale

A complete bullion file should include:

• serial number that matches the number stamped on the bar;
• stated weight in grams, kilograms, or troy ounces;
• silver fineness, commonly marked as 999;
• refinery or mint name and official logo;
• assayer signature or certification mark where applicable;
• product dimensions and identifying design details;
• certificate condition and absence of unauthorised changes.

The best-run platforms combine these ownership details with allocated vault storage and app-based account access. Buyers can review products from accredited sources, track their holdings, and retain records that support verification when they later sell or request physical delivery.

The post How Serial Numbers and Assay Details Protect Silver Bullion Buyers appeared first on LAFFAZ.

Asaya, a direct-to-consumer skincare brand, has raised ₹88 crore ($9.2 million) from RPSG Capital, OTP Ventures, Huddle Ventures, Hyperscale Ventures and 72 Ventures at a post-money valuation of ₹400 crore, the company said on August 24. The round mixed primary capital with a secondary component that let some early angel investors exit part of their holdings; the split between the two was not disclosed.

The Bengaluru-based company had previously raised ₹28 crore in a pre-Series A round led by RPSG Capital in September 2025, at a reported valuation of about ₹138 crore. The step-up to ₹400 crore in under a year is close to three times that mark. Founded in 2021 by Neeraj Biyani, Eeti Sharma and Mandeep Singh Bhatia, Asaya sells serums, even-tone creams, cleansers, sunscreens and body sprays targeting hyperpigmentation, dehydration and acne, sold through its own website, quick-commerce platforms, marketplaces including Nykaa and Myntra, and a growing set of offline retail partnerships. Biyani, the chief executive, was earlier a co-founder of the beverage brand Paper Boat.

At the centre of Asaya’s pitch is MelaMe, a proprietary, patent-pending molecule the company says is formulated specifically to address pigmentation and uneven tone on Indian, melanin-rich skin — a segment the brand argues mainstream, Western-formulated skincare has long underserved.

“We’ll be directing almost a fifth of the funding towards R&D, with the rest split across product-line expansion and geographic and channel growth.” said Neeraj Biyani, Co-founder, Asaya

Asaya says its revenue has grown 16x since the September round and that it now operates at an annualised revenue run rate of ₹100 crore, with a target of ₹200 crore within 18 months. Around a fifth of the fresh capital will go towards research and development, with the rest split across product-line expansion, distribution and hiring. Co-founder Biyani struck a similarly confident note on where the company now stands financially.

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Airbound, a Bengaluru-based aerospace startup, has raised $37 million in a Series A round led by Greenoaks, with participation from DoorDash, angel investor Lachy Groom, Lightspeed and Humba Ventures, the company confirmed on August 25. The round takes Airbound’s total funding to nearly $50 million since it was founded in 2023, and follows an $8.65 million seed round led by Groom less than a year earlier. No valuation was disclosed.

Founded by Naman Pushp, who began building drones at age 15, Airbound designs vertical-take-off “tail-sitter” aircraft engineered to weigh less than the cargo they carry — a ratio the company says runs roughly three times better than the industry norm of 4:1. Its current aircraft, TRT, weighs about 1.5 kg and carries roughly 1 kg; a next-generation model is designed to weigh about 2.99 kg and carry up to 4.9 kg. The company positions itself as an aircraft manufacturer rather than a delivery operator, designing and building in a 43,000 sq ft Bengaluru facility and selling the hardware to logistics operators.

Airbound says it has completed more than 13,000 autonomous flights across Bengaluru and Guntur, including over 1,000 with the Narayana Health hospital network flying diagnostic samples between facilities. It has also signed a commercial deployment agreement with the Andhra Pradesh government to build an aerial network across Amaravati, Vijayawada and Guntur, with a stated target of 10,000 daily flights across retail, e-commerce and healthcare. Production has scaled from two aircraft a month to two a day over the past year, with a near-term target of 20 a day, according to the company.

The gap between that pitch and proof remains wide. Airbound’s flagship healthcare deployment still runs largely on a single route, and the 10,000-daily-flight target in Andhra Pradesh depends on manufacturing scale, airspace management and, above all, regulatory approval for beyond-visual-line-of-sight (BVLOS) flight that India is still building a framework for. DoorDash’s participation in a hardware-heavy Series A suggests last-mile logistics players are hedging against ground-delivery economics plateauing — but until BVLOS clearance catches up with the aircraft, Airbound’s cost-parity claim stays a claim rather than a demonstrated unit economic.

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Ringg AI, a Bengaluru-based enterprise voice AI startup, has raised $10 million in an extended Series A round led by Peak XV Partners, with existing backers Arkam Ventures and Capital 2b also participating, the company said on August 26. The extension takes the total size of Ringg’s Series A, first closed at $5.5 million in January 2026, to $15.5 million. No valuation was disclosed.

Founded in October 2023 by Siddharth Shankar Tripathi, Utkarsh Shukla and Kali Charan Vemuru, Ringg builds AI agents that automate customer conversations for enterprises across voice calls, WhatsApp and browser-based workflows. Tripathi previously worked at Groww and Flipkart; Shukla at Blinkit and Atlan; and Vemuru at Flipkart. The company is also backed by fintech entrepreneur Kunal Shah and the Groww Founder Fund.

Ringg began life as a text-to-speech company called DesiVocal, but pivoted to enterprise voice agents after finding the cost of training its own speech models difficult to sustain as a standalone product. It has since rebuilt that capability on its own terms: the company develops proprietary speech recognition and generation models in-house, and its platform routes tasks across different models depending on the workflow. It now processes roughly 20 million call attempts a month, with voice still accounting for more than 70% of the business, and counts Flipkart, Practo, Groww, PolicyBazaar and Shell among its clients. Its agents are deployed across 1,200 Practo clinics for appointment booking and post-visit follow-ups.

The new capital will fund an expansion into more complex, regulated workflows — healthcare appointment booking, ecommerce cart recovery, and fintech onboarding and KYC — that the founders see as more defensible than the high-volume outbound calling and lead qualification work Ringg started with.

“Nobody buys us because the demo sounds good,” said Siddharth Tripathi, founder and CEO of Ringg AI. “They buy us because onboarding improves, resolution times fall, or qualified leads start showing up in the CRM without someone having to make the call. Enterprises should not have to buy a voice layer and then stitch the rest together. We own the loop from conversation to action to evaluation to improvement.”

That candour about commoditisation risk is echoed by the startup’s newest investor. Peak XV principal Rishen Kapoor pointed to Ringg’s in-house model stack as the reason it can take on harder enterprise mandates rather than compete purely on price.

“Because of the technical capabilities, they can actually do these hard-won enterprise workflows end to end. They can complete these higher-value tasks like merchant onboarding, like L1 and L2 support, with quality and with consistency,” Kapoor said in a statement to TechCrunch

Bengaluru’s voice-AI field is crowded and well capitalised, with rivals including Sarvam and Gnani chasing the same enterprise demand, and the category is reported to have drawn over $250 million in the region this year. Ringg’s 40-person team has grown by more than 15 in the past three months. Its bet is that owning the model layer, rather than reselling third-party AI, buys it a durable latency and cost edge as it moves up the value chain — a wager that carries the same cost pressure that forced its pivot away from DesiVocal in the first place.

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Thane, Maharashtra-based InspeCity, a space-tech startup incubated at IIT Bombay, has raised ₹100 crore (about $10.5 million) in a pre-Series A round co-led by Speciale Invest and veteran stock-picker Ashish Kacholia, the company confirmed on August 27. Antler India, Antler Elevate, Shastra VC and angel investor Manish Gandhi also participated, and InspeCity has not disclosed a post-money valuation for the round.

The raise follows a $5.6 million seed round in May 2025, also led by Kacholia, and a $1.5 million pre-seed round led by Speciale Invest in 2023. Total funding now stands near ₹150 crore. InspeCity said the capital will go towards flight-qualifying its in-space servicing technology and executing four in-orbit missions over the next 12 to 18 months, under a roadmap it calls RIG-X, VEDA-X and SAMA-X.

Founded in 2022 by Arindrajit Chowdhury, an IIT Bombay professor, Tausif Shaikh, Sanket Dash, and Ananth Ramesh, InspeCity builds in-space servicing, assembly and manufacturing (ISAM) technology aimed at extending satellite lifespans and cleanly deorbiting spacecraft at end of life. Its platform, VEDA (Vehicle for Life-Extension and Deorbiting Activities), is designed to rendezvous with a satellite, dock with it, and either refuel and reposition it or guide it to a controlled deorbit. The company has broken the problem into modules — GITA for propulsion, CHAKSU for sensing and navigation, RAMA for robotic manipulation, and SPARSH for docking and in-orbit refuelling — each validated separately before being assembled into a full servicing mission.

The four planned missions will test rendezvous and proximity operations, propulsion and robotics in orbit, InspeCity has said, as it works towards flight qualification for VEDA ahead of a demonstration mission previously slated for 2027. The company has also won contracts under India’s iDEX defence innovation programme and formed partnerships with space-tech players in Japan and Taiwan, giving it an early, if narrow, revenue base in government and defence R&D work while the commercial servicing market remains unproven.

Globally, InspeCity is chasing a market that companies including ClearSpace, Starfish Space and Astroscale are also pursuing, several with more capital and flight heritage already logged. In India, most well-funded space-tech names — Skyroot Aerospace, which became the country’s first spacetech unicorn earlier this year, and Agnikul among them — are concentrated in launch, leaving satellite servicing a comparatively open niche domestically. The compressed timeline is the clearest risk in the round: deep-tech hardware routinely slips, and a single failed in-orbit demonstration could reset both the roadmap and the case for InspeCity’s next fundraise.

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Battery Smart, the electric-vehicle battery-swapping startup, has raised ₹185.5 crore ($19.5 million) in a Series C round led by existing investor Rising Tide Ventures, with participation from Ecosystem Integrity Fund and Blume Ventures, according to the company’s filings with the Registrar of Companies (RoC). The round was structured as 34,094 Series C compulsorily convertible preference shares at an issue price of ₹54,407 each, raised across two tranches of roughly ₹97 crore and ₹88 crore. Rising Tide Ventures contributed ₹112 crore, Ecosystem Integrity Fund ₹49 crore and Blume Ventures ₹25 crore.

Entrackr estimates the round values Battery Smart at around ₹4,075 crore ($430 million) post-money; the company has not officially confirmed a valuation. That estimate sits below the roughly $450 million the company was reported to have been valued at during its extended Series B round in mid-2025, making this a flat-to-down round by that measure. The raise follows a busy financing stretch: a ₹66 crore pre-Series C round in March 2026 from Acacia Inclusion, Blume Ventures and PC-SBI Kurashi Visionary Fund, and $15 million in debt from Mirova in April. Battery Smart has now raised more than $211 million to date, with backers including Tiger Global, Blume Ventures and Ecosystem Integrity Fund.

Founded in 2019 by Pulkit Khurana and Siddharth Sikka, both IIT Kanpur alumni, Gurugram-based Battery Smart runs a battery-swapping network for electric two- and three-wheelers, letting gig-economy drivers swap a depleted battery for a charged one in minutes rather than bearing the upfront cost of ownership or the downtime of charging. The company said the fresh proceeds will support business expansion, capital expenditure, working capital and general corporate purposes, and it is reported to be preparing to file draft IPO papers around September or October.

The operating numbers behind the raise are improving even as the valuation has not kept pace: per its RoC filings, Battery Smart’s FY26 revenue rose 43.8% to ₹358 crore, while its net loss narrowed to ₹23.55 crore, with the company reported to have reached operational break-even during the year. That combination — a capital-intensive, asset-heavy swapping network approaching profitability just as it heads towards a public listing — is likely to anchor the pitch in its IPO prospectus.

The tension in the round is that an improving business and a flat-to-down price are pointing in different directions, which typically signals that the company’s earlier private mark ran ahead of what public-market investors will pay for infrastructure-heavy EV assets. Battery Smart competes with Sun Mobility, VoltUp and Mooving in swapping, and with steadily improving fast-charging as the alternative technology path. With an IPO filing expected within weeks, the company has little room for the FY26 break-even claim to slip when its draft papers are scrutinised against the June-quarter numbers.

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NeoGeo, a Gurugram-based geospatial technology startup, has raised $20 million in a Series A round co-led by Neev II Fund and Aavishkaar Capital, the investment arm of the Aavishkaar Group. No other investors were named, and valuation, dilution, and board composition have not been disclosed.

The company said it will use the funds to expand its platform and product portfolio through R&D, enter international markets across the Middle East and the Americas, and strengthen its team. It is a large step up from NeoGeo’s only prior disclosed round, a roughly $1.55 million seed in December 2024 — more than tenfold what it had raised before.

Founded in 2019 by Sreeramam GV, NeoGeo describes itself as a full-stack geospatial system integrator spanning data acquisition through satellite imagery, LiDAR, drones and ground surveys, through to AI/ML analytics and industry software under platforms including OptiFleet, GeoBalance, UrbanVista and InfraSync. The company says it has executed more than 200 projects, mapped over 5 lakh sq km, and manages more than 550 CORS stations, figures that are company-stated.

Also Read: Tenet Diagnostics Lands $30M From Tata Capital, Blue Earth

NeoGeo sits in the middle of the geospatial value chain rather than at either end: it neither owns a satellite constellation nor simply resells mapping software, instead stitching acquisition, processing and analytics into decision-ready outputs for governments and enterprises. Its revenue today is largely project-based, and its CORS network adds an infrastructure layer that can carry ongoing service revenue rather than one-off project fees — but delivery capacity and recurring software revenue are different economics, and the Series A is really a bet on turning the former into the latter.

That transition is unproven. India’s geospatial demand leans heavily on government and public-sector buyers, which is durable but slow-paying and tender-driven, and does not obviously translate to the Middle East and the Americas that NeoGeo now plans to enter. It also competes with better-funded, satellite-owning Earth-observation names such as SatSure and Pixxel. NeoGeo’s edge is breadth across the value chain; the risk is that breadth is expensive to sustain on a single large round without recurring revenue to show for it before the next one.

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Tenet Diagnostics has raised approximately $30 million from Tata Capital Healthcare Fund III and Blue Earth Capital, a Switzerland-based impact investor. The equity stake, valuation, and split between the two investors have not been disclosed, and no board changes have been stated.

The capital flows into Tenet Medcorp Private Limited, which trades as Tenet Diagnostics. Talks between the two sides were first reported in March 2026, making this a five-month process from disclosure to close, and the deal is among the first investments from Tata Capital’s third healthcare fund since its first close earlier this year. The company said the money will help it deepen its footprint across India and expand access to diagnostics.

Founded in 2016 by Hanumantha Rao Ch, Surendranath C, Vinod P Nair, and Ram Pap Rao A, Tenet now runs a network of pathology and radiology centres across Telangana, Andhra Pradesh, Karnataka, Maharashtra, Bihar, Uttar Pradesh, Jharkhand and Odisha, offering imaging, lab testing, cardiology and neurology services including MRI, CT, PET-CT and mammography. The most recent public financials are from September 2023, when the company reported 100% year-on-year turnover growth and expected to cross ₹150 crore that year across 25 locations in eight states; no revenue or centre count has been published since.

Diagnostics is a capital business dressed as a services one. Pathology labs are cheap to open, but an MRI or PET-CT machine costs several crore and needs a shielded room and a radiologist, which is why profitability in the category is a question of utilisation rather than pricing. Tenet’s expansion into states like Bihar, Jharkhand and Odisha, where advanced imaging is thin, is a bet that being early with a PET-CT in an underserved district is a durable edge, since the next operator into that market faces the same equipment bill against a smaller share of demand.

The investor pairing is worth reading closely: Blue Earth Capital is a limited partner in Tata Capital’s healthcare fund rather than an independent co-investor, and the two firms have structured a round this way before, in a $9 million investment into Apex Kidney Care in early 2025. Three years without an updated revenue figure means Tenet is being priced against a target rather than a result.

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Traditional search engines are no longer the sole gatekeepers of digital visibility. Today, consumers rely heavily on answer engines like ChatGPT, Perplexity, and Google’s AI Overviews to make purchasing decisions. If your brand is not appearing in these conversational answers, your digital presence is essentially invisible.

This shift has made traditional optimization techniques insufficient on their own. Businesses must now adopt specialized GEO services to ensure they remain relevant.

To fix invisible brand mentions, you need targeted strategies that align with how artificial intelligence processes data. This blog explores critical GEO services that can secure your brand’s position in the AI-first era.

Core GEO Services That Improve AI Search Visibility

Here are the core GEO services that help improve your brand’s visibility, credibility, and discoverability across AI-powered search platforms:

1. AI-crawlable Content Audits and Optimization

AI engines do not read content the way human users or traditional search crawlers do. They scan for factual integrity, structural clarity, and direct answers to complex user queries.

A foundational component of GEO services is a comprehensive content audit tailored specifically for generative models. This process reviews your existing digital assets to ensure they possess an AI-friendly structure.

Many businesses invest heavily in traditional SEO services in India to rank on the first page of search results. However, high rankings do not guarantee that an AI model will cite your content. Generative engines look for concise definitions, structured data, and authoritative data blocks. In a controlled study, researchers at Princeton University have found that adding citations, statistics, and quotations to content could lift its visibility in generative engine responses by as much as 40 percent.

Professional GEO services reformat your blogs, articles, and landing pages into highly crawlable formats. This optimization makes it easy for LLMs (Large Language Models) to extract your brand information and present it as a primary solution.

2. Entity Recognition and Knowledge Graph Alignment

Generative models rely heavily on established knowledge graphs to verify information before presenting it to users. If your brand lacks a clear semantic footprint, AI engines will treat your business as an unverified source.

Professional GEO services focus on strengthening your brand’s entity recognition across the digital ecosystem. This involves aligning your corporate data with trusted third-party databases, independent registries, and structured schema markup.

When you partner with an agency providing expert SEO services in India, they ensure your technical foundations are flawless. Advanced GEO services take this further by mapping your brand relations, products, and core expertise into a format that AI engines can validate instantly.

This alignment ensures that when an AI engine searches for industry leaders, your brand is recognized as a factual and verified entity.

3. Digital PR and Citation Authority Building

Traditional search engines use backlinks primarily as popularity votes to determine page authority. Generative engines view links through a slightly different lens, looking for credible citations that validate specific facts.

AI models favor brands that possess strong digital credibility and consistent mentions across reputable news platforms, trade publications, and academic sources. Earning these high-value citations requires a dedicated digital PR strategy. An analysis of nearly 69,000 real Google searches by the Pew Research Center found that 88 percent of AI-generated summaries cite three or more sources rather than relying on a single reference, underlining how much weight generative engines place on a broad base of credible citations.

By leveraging targeted GEO services, your business can execute PR campaigns that specifically aim for algorithmic trust. This process goes beyond standard link acquisition. It focuses on building a network of authoritative mentions that AI models naturally reference when generating summaries.

This extensive digital footprint ensures your business is actively cited as a trusted answer rather than being left out of the conversational loop.

Also Read: Adapting to AI-Powered Search: Building Growth While Preserving Your Brand

4. Visibility Tracking and Share of Voice Monitoring

You cannot optimize what you do not measure. Tracking visibility in traditional search relies on keyword rankings, but tracking visibility in AI search requires monitoring actual algorithmic citations.

Advanced GEO services utilize proprietary tools to track how often your brand appears in conversational answers. These services benchmark your brand against top competitors to analyze your true share of voice across platforms like Gemini, ChatGPT, and Perplexity. The stakes are already substantial: the same Pew Research Center study found that 58 percent of surveyed adults encountered at least one Google search with an AI-generated summary in a single month, meaning a majority of queries now bypass the traditional results list entirely.

Regular monitoring allows businesses to understand which pieces of content are successfully earning citations and which ones remain invisible. Agencies offering comprehensive SEO services in India can integrate these advanced tracking metrics into their broader digital marketing reports.

By continuously analyzing these generative search metrics, your marketing team can refine its content strategy based on real-time AI behavior data.

5. Category and Location-based AI Planning

Every industry has a unique digital footprint, meaning that a retail brand requires a different optimization approach than a B2B enterprise software company.

Customized GEO services provide tailored plans designed around your specific business category and geographic target market. AI engines synthesize vast amounts of localized data to answer user prompts that contain explicit or implicit geographical intent.

If your business relies on local or regional customers, your conversational data must match local search patterns perfectly. Integrating localized intent into your generative search plan ensures that your business displays prominently in regional AI summaries.

Leading providers of SEO services in India help brands blend local search parameters with advanced generative optimization techniques. This comprehensive approach ensures your brand remains highly visible, citable, and authoritative across both local and global AI search platforms.

Secure Your Place in the AI Search Era

To maintain digital visibility, modern enterprises must invest in specialized GEO services that align with conversational AI models. Transforming your digital presence requires deep expertise, advanced visibility tracking tools, and a performance-first approach to content authority.

Partnering with a trusted GEO agency can help businesses strengthen their presence across AI-powered search platforms while protecting long-term organic visibility. The right partner will provide the end-to-end solutions, custom strategies, and proprietary tracking tools needed to ensure your brand remains the preferred answer in AI search summaries.

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Education benefits pay for some or all of an employee’s study, and US employers increasingly treat them as a reason people stay rather than a line on a benefits summary. The category stretches across tuition assistance for degrees, funding for certifications and short courses, and contributions toward student loans an employee already carries. What ties them together is that the employee walks away with something portable and personally valuable, which is unusual among workplace benefits.

Attention tends to arrive when turnover costs start hurting. Replacing a single employee can run from one-half to two times that person’s annual salary, according to Gallup, which puts real numbers behind the intuition that losing a skilled worker often costs more than funding a year of somebody’s study. Program design decides whether any of that retention effect materializes, and most of the difference comes down to how the money reaches the employee and who can realistically make use of it.

Models that remove the upfront cost

Reimbursement is the older approach, where the employee pays tuition, passes the course and claims the money back months later, which quietly rules out anyone unable to float a few thousand dollars. Direct billing removes that barrier by sending payment to the school from the employer or the plan administrator. Large-scale programs in the US work this way, and education benefits for union members are usually negotiated at the organization level, with the school network and covered amounts agreed before any individual enrolls.

Why the benefit holds people

Retention improves when study connects to somewhere the employee can actually go, so a finished qualification maps onto a role, a pay band or an internal move rather than sitting on a resume. Programs left alone drift out of usefulness, and close to four in ten employers say their tuition assistance hasn’t been reviewed in three years, which shows up as outdated school lists and caps that no longer cover much of a course. Tracking promotion and turnover among participants against everyone else is what keeps finance funding it.

Also Read: What Skills Do Freshers Need to Land Their First AI/ML Job

Where uptake usually breaks down

Most US employers already offer something educational. Roughly 48% of organizations offer undergraduate or graduate tuition assistance, according to SHRM’s Employee Benefits Survey, so simply having the benefit isn’t a differentiator anymore. Take-up is where programs quietly fail, and the reasons are consistent enough to check against your own policy:

• Eligibility waits that push access past the point where most turnover happens
• Clawback clauses demanding repayment if someone leaves within a year or two
• Approved school lists that don’t include a relevant program
• No workload or scheduling adjustment, leaving study to compete with overtime

The gap between offering a benefit and people actually using it is well documented. Separate research from the same U.S. Chamber Foundation survey found that 44% of employers offered no additional resources — like adjusted schedules — to help employees actually pursue education while working, which is a large share of programs asking people to study on top of a full workload rather than instead of part of it.

What it costs to get wrong

The retention math only works if the program is actually reaching people who might otherwise leave. Turnover isn’t a marginal cost: Gallup estimates that voluntary turnover costs US businesses more than $1 trillion a year in recruiting, hiring, onboarding, training and lost productivity during transitions. Against that backdrop, an education benefit that sits unused because of a six-month waiting period or a clawback clause isn’t neutral — it’s a retention tool employers are already paying for but not deploying.

Making the program worth the spend

Communication does more work here than budget size, because a generous benefit nobody knows about performs identically to no benefit at all. Managers are the bottleneck in most organizations, so they need the eligibility rules well enough to raise the option in a development conversation without checking with HR. Pairing funding with protected study hours or a lighter rotation during exams costs little and removes the objection most employees actually have, which is time rather than money.

Look at who has used the benefit over the past two years and what happened to them afterward. If participants cluster in one department, or if the people finishing qualifications are the ones leaving, the problem sits in the progression routes rather than the funding. A benefit that pays for a credential nobody uses internally is functionally a resignation subsidy — the fix is rarely more money, it’s a clearer route from the finished course to the next role.

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BlissClub, the Bengaluru-based direct-to-consumer athleisure brand, has raised ₹160 crore (roughly $16.8 million) in a Series B round led by Singularity AMC, with founder Minu Margeret and Meesho founder Vidit Aatrey participating as individual investors alongside returning backers Elevation Capital and Eight Roads Ventures.

The company has not disclosed the valuation, the equity diluted, or how the ₹160 crore splits between Singularity AMC and the other participants, framing the use of funds instead around expansion into new categories, a larger offline retail footprint, product development and hiring.

It is BlissClub’s largest round to date and the first time a new institutional investor has entered its cap table since 2022, with both existing backers choosing to return rather than exit. The company’s last raise was a $15 million Series A in May 2022 led by Eight Roads Ventures with Elevation Capital participating, which followed a $2.25 million seed round in May 2021.

Also Read: Bakingo Raises ₹100 Cr Series B From Faering Capital

Founded in 2020 by Margeret, BlissClub began with technical activewear built specifically for Indian women and has since grown into an omnichannel operation spanning its own website, online marketplaces and more than 40 physical stores, adding a menswear line in recent months.

The round lands on the back of a financial year that strengthens BlissClub’s case for the retail bet it is now making. Operating revenue in FY25 grew 51 percent to ₹131.5 crore from ₹87 crore in FY24, and the company has said it more than halved its losses over the same period on lower employee costs, though it has not disclosed the absolute loss figure.

Revenue climbing while losses narrow is typically the strongest signal a D2C brand can offer that its unit economics are improving rather than being propped up by spend, and it is likely the number that persuaded Singularity AMC and the returning investors to back a larger, capital-heavier phase of the business.

That phase now shifts the brand’s biggest test from digital acquisition to physical retail economics. BlissClub built its identity online, competing in a category — activewear — where fabric and cut are easy to copy and where Nike, Adidas and Puma sit above it on distribution while a widening field of domestic labels compete below on price.

Forty stores scaling on ₹160 crore is a materially different cost structure from the e-commerce model that produced the FY25 numbers. With FY26 accounts still unfiled, whether owned retail deepens BlissClub’s margins or erodes the progress it just reported remains the open question the round is meant to answer.

Also Read: She Built the Community Before She Built the Leggings

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Gurugram-based online bakery brand Bakingo has raised ₹100 crore (~$10.5 million) in a Series B round from its existing investor, private equity firm Faering Capital, at a valuation reported to be 2.6 times higher than its previous round.

Bakingo was founded in 2016 by Suman Patra, Shrey Sehgal and Himanshu Chawla, growing out of FlowerAura, the gifting e-commerce company the same founders built first — a lineage central to how the bakery still operates. Gifting gave Bakingo a ready demand channel and an understanding of occasion-led buying, where customers order ahead and value reliability over the lowest price.

The raise lands as branded, vertically integrated bakery brands try to hold ground on two fronts at once. Theobroma, Monginis and a field of regional chains compete on brand and freshness, while Blinkit, Swiggy and Zomato have pushed hard into instant cake delivery, turning speed into the axis of competition and pressuring any model built around a scheduled order. Bakingo runs its own network of more than 100 kitchens across over 30 cities, producing over 400 cake designs sold through its website, its sister gifting platform FlowerAura, and quick-commerce channels — a dark-kitchen footprint that is an asset against the first group of rivals and a potential liability against the second if consumers shift decisively toward instant delivery.

Also Read: Discovered Materials Raises $9M Seed Led by Lightspeed India

Following the allotment, Faering holds a 26.31 percent stake in Bakingo. By Entrackr’s analysis of the RoC filing, the round values the company at ₹1,643 crore ($173 million), about 2.6 times the ₹627 crore at which it raised its previous round — a $16 million investment also from Faering in November 2023, which was Bakingo’s first external funding after seven years of bootstrapped operation and was reported then at a valuation of around ₹571 crore. Bakingo has not disclosed the equity dilution details, the primary-secondary split, or a specific use for the fresh capital beyond general business requirements and expansion. In FY25, the company reported standalone revenue of ₹300 crore against a net loss of ₹16.5 crore; revenue has climbed steadily from ₹94.6 crore in FY23, but the loss has widened from ₹0.8 crore over the same span as the kitchen network expanded, and FY26 accounts have not yet been filed.

A round funded entirely by the incumbent investor, with no new institutional name attached, can read as efficient continuity or as limited outside appetite at this valuation — the filing does not say which. Bakingo’s edge is that gifting demand from FlowerAura arrives without paid acquisition, and owning its kitchens captures margin an aggregator cannot, in a category where brand trust and reliable delivery matter more than price. What the fresh ₹100 crore has to prove is whether that structure can turn into profitability at scale, or whether it simply funds another leg of expansion that widens the loss before it narrows it.

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San Francisco-based deep-tech startup Discovered Materials has raised $9 million (₹85 crore) in a seed round led by Lightspeed India Partners, with participation from Y Combinator and Peak XV Partners, alongside angel investors including Paul Graham, Gokul Rajaram, and Thariq Shihipar. The round, announced on 10 August 2026, is Discovered Materials’ first institutional funding, and the company has not disclosed the valuation at which it was raised.

The startup is chasing a bottleneck that has quietly become one of the AI industry’s most expensive problems. Modern AI chips shed heat at fluxes exceeding 140 watts per square centimetre, hotter than a spacecraft on re-entry, and that heat drains much of the power and water a data centre consumes. Finding thermally conductive materials that can cool 3D chip packaging has historically taken over a decade of lab work, a timeline sharply at odds with the pace of the chip build-out itself. Discovered Materials’ bet is that swarms of AI agents, built on frontier models in a custom harness, can propose thousands of candidate materials a day, with in-house physics simulations filtering them by stability and thermal performance before anything reaches a lab.

Also Read: Yulu Raises $93M Series C Led by GEF Capital

The company emerged from Y Combinator’s Spring 2026 batch, founded the same year by Akash Ramdas and Advaith Sridhar, who met more than a decade ago at IIT Madras. Ramdas holds a PhD in materials science from Stanford, where his work on nanoscale interconnects fed into roadmaps at Intel and TSMC; Sridhar, the chief executive, studied AI at Carnegie Mellon and built autonomous agents at Persona AI and Luma Labs before this. The capital raised will go toward expanding the team and laboratory and scaling the company’s research agents. Alongside the round, Discovered Materials released the Material Discovery Bench, a benchmark for how frontier AI systems perform on real semiconductor materials problems — a move that positions the young company as a party defining how the field gets measured, independent of any single model generation.

The funding does not settle the harder question. Discovered Materials is months old, pre-revenue and small, and its claim of producing thermal materials in three months that match products which took years to develop is the company’s own and remains unverified. Generating candidates fast is the part AI makes easy; validating a material in a fab and persuading a conservative chipmaker to adopt it is the multi-year, expensive part that no AI-discovered material has yet cleared commercially. The startup is also entering a field where Microsoft’s MatterGen, Google DeepMind’s GNoME and well-funded materials-AI rivals are chasing the same compression of materials discovery with considerably deeper resources, which makes its narrow focus on thermal materials for chip packaging — where one founder already carries production credibility — a sensible wedge rather than a broad bet.

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Bengaluru-based electric mobility-as-a-service platform Yulu has raised $93 million in a Series C round combining $63 million in equity, led by GEF Capital Partners, with $30 million in debt. The round, announced on 12 August 2026, is reported to value Yulu at about $170 million post-money; chief executive Amit Gupta declined to confirm the figure but did not dispute it. About $5.5 million of the equity bought out early seed investors nearing the end of their fund life, rather than flowing into the business, Gupta said, and existing strategic backers Bajaj Auto and Magna International did not participate, waiving their pre-emptive rights to let GEF acquire its target stake.

The round lands as shared electric two-wheelers have found a job well beyond urban commuting: the delivery layer under India’s ten-minute grocery boom. Yulu’s vehicles now handle more than 750,000 doorstep deliveries a day and account for over 15 percent of quick-commerce deliveries across India’s four largest metros, turning what began as a shared-bike service into logistics infrastructure for platforms like Blinkit, Zepto and Swiggy Instamart. The company owns its roughly 50,000-vehicle fleet outright and rents it out by the day or trip, an asset-heavy model in which battery swapping through Yuma, its joint venture with Magna, keeps vehicles earning instead of charging — and explains why $30 million of this round arrived as debt rather than equity, since fleet financing is typically cheaper than selling shares.

Founded in 2017 by Amit Gupta, RK Misra, Naveen Dachuri and Anuj Tewari, Yulu has now raised more than $228 million since inception, including an $82 million Series B led by Magna in September 2022 and $19.25 million from Magna and Bajaj in February 2024. The fresh capital is earmarked to quadruple the active fleet to 200,000 electric vehicles over two years, expand into new urban-mobility use cases including a higher-payload scooter for e-commerce parcels, and prepare the company for a potential public listing. Operating revenue nearly doubled to ₹237.4 crore in FY25 from ₹119.9 crore in FY24, and Yulu says it has been EBITDA-positive since April 2025, even as it posted a ₹126 crore net loss for the year, down 12 percent from the prior year.

The terms complicate the growth story the fleet numbers tell. A reported post-money of about $170 million, nine years after founding and against more than $200 million raised, looks flat to down measured against valuations ascribed to Yulu in 2025, and a round partly used to buy out early investors while two strategic backers sat out is consistent with a deal structured for a new entrant and an exit for old ones, whatever the framing. What Yulu has that few mobility peers can claim is a genuine operating turn: positive EBITDA, near-doubled revenue and a captive, if concentrated, demand source in quick commerce. The risk sitting underneath is that same concentration — a handful of cash-burning delivery platforms could bring logistics in-house or squeeze rates — colliding with the capital intensity of quadrupling a fleet before the business converts EBITDA breakeven into sustained net profit.

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Traditional search engine optimization (SEO) tactics are no longer enough because of the rise of modern search systems that use AI. To remain visible in search, brands have to design their content so that it can be as easily read by both machines and humans. In this article, we discuss how AI search has shifted traditional SEO logic and what that means for both growing and preserving your brand.

How AI Search Has Shifted Traditional SEO Logic

The original goal of search engine optimization, or SEO, was to rank highly for specific keywords. Ranking first for the most important queries was essentially the finish line. As a result, traditional SEO models focused on strategies like placing the right keywords in content. Search engines would then match a user’s search terms to those placed keywords.

This keyword-based approach is not enough because almost every modern search engine now uses AI to read online content and generate direct answers. SEO success was also measured mainly through metrics like click-through rates and organic traffic. In the age of AI search, these metrics give an incomplete picture of online visibility.

Due to this shift in search technology, the new goal of modern search optimization strategies is to create content that can be easily digested and summarized by AI-powered search systems. In fact, many users now conduct zero-click searches where they never have to click on any search engine result pages (SERPs) — a June 2026 SparkToro and Similarweb study found that 68% of US Google searches ended without a click in the first four months of the year, the fastest two-year acceleration the researchers have recorded. This heavy reliance on AI-generated answers means that brand mentions are the most important metric for AI visibility success.

Optimizing Your Content for AI Visibility

Identifying the Right Prompts

The first way to optimize your content for AI visibility is by identifying the right prompts that users actually search. Think of some of the most important questions that buyers will ask before purchasing one of your products. Categorize these prompts based on how informed your customer is at each stage of the decision-making process. Prioritize prompts with the most commercial intent, and make sure that your content answers these prompts.

Mapping Query Fan-Outs

When an AI-powered search engine is asked to search the internet for information, it often conducts several adjacent related searches in addition to the target query. It then digests the answers to this query fan-out in order to generate a comprehensive answer for the user’s main question. When you are testing prompts, use in-model or third-party tools to see what additional searches an LLM is using. That info is invaluable for better focusing your content.

Extractable Passages

Instead of just ranking pages, AI-powered search systems are looking for passages that they can extract to answer the query fan-outs for a user’s main query. They are still drawing from a retrieval pool built on some traditional SEO basics, but every page your brand posts should be made of extractable passages. If you do, these systems can map individual sections cleanly onto the sub-queries that the LLM generates.

To ensure extractable passages, you should organize your content into short and easy-to-read sections. It is also helpful to use structures that AI systems find particularly easy to parse. These include FAQ sections, bulleted lists, content broken into subheadings under the main heading, etc.

Brand Authority

Search engines are also more likely to surface your content if they believe that your brand is an authoritative source. The first step to building authority is to focus your content on fact-based conclusions and analysis. At the same time, you should also provide the most accurate and comprehensive answer to potential user queries.

Brands are also seen as more authoritative if they have a consistent and specific content focus, because that demonstrates topical authority. Getting backlinks from trusted and established sources in your industry will also help convince AI systems that your site is authoritative.

Technical SEO

Technical SEO is about optimizing your website’s infrastructure so that AI-powered search systems can easily crawl and index your content. Everything should load quickly, content needs to be mobile-friendly, and there should be clear headings and structures. Poor loading times, coding errors, and structure issues will make your content harder for machines to navigate.

When coding your site, a main focus should be placed on making everything easy to access and having canonical tags so that there is no chance of duplicate content. If this part of AI visibility sounds too daunting, you and your team can hire a premium AEO agency that specializes in technical SEO.

Protecting Your Brand in AI Search

Cybersecurity Software

The easiest way to protect your brand in the era of AI search is by installing the right cybersecurity software. Install a multi-pronged security program that blocks malicious AI bots from accessing your content while still allowing AI-powered search systems to access and digest content as needed. Such cybersecurity software blocks bot attacks, separates authentic users out, and audits your content to see what percentage of your content is viewable by AI. Customize which program you use based on your brand’s needs.

Internal AI Guardrails

At the same time, it is also best practice to install some basic internal guardrails around AI use. Set clear policies on when AI can be used to create or edit content, and try your best to exclude even light AI editing when creating landing pages and other crucial content. Double-check that only high-quality AI tools are being used and that your brand’s content is not being secretly used to train AI.

Copyrighting and Trademarking

Your brand can also be protected from AI theft and replication through standard copyrighting and trademarking. Start by registering your brand’s logos, domain names, products, and even certain parts of your content. After that registration is complete, you can also use certain trademark-tracking tools to help prevent your content from being scraped.

Key Takeaways

The implementation of AI has totally shifted the online search landscape, and many users rely on generated answers instead of clicking through search engine results pages. Instead of ranking high in search, the goal of modern SEO strategies is now to optimize content so that it can be easily digested and summarized by AI systems. Brands will experience better growth if they adapt to this new goal, and they can simultaneously protect their content through custom cybersecurity software, internal AI guardrails, and copyrighting.

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For most of the last decade, a D2C founder’s growth story followed a predictable arc: launch in Bengaluru or Mumbai, chase Instagram-led discovery among a young, high-income metro audience, then “expand” into smaller cities once the brand had proven itself. That sequence is starting to invert. According to Unicommerce’s FY26 analysis of over 400 million order items across more than 6,000 digitally native brands, Tier-2 and Tier-3 cities accounted for nearly two-thirds of new D2C orders in the financial year, and around 60 percent of incremental gross merchandise value over the previous year. India’s overall D2C order volumes grew 33 percent year-on-year, with GMV up 32 percent, in a market currently sized between $10 billion and $12 billion and projected to reach roughly $60 billion by 2030.

The data behind the shift

The Unicommerce numbers aren’t an isolated data point. A separate industry study, SGA PR’s “Pulse 2026” report, unveiled at the Bharat Startup Summit, found that categories once considered strictly metro business — protein nutrition, premium skincare, wellness supplements — are now seeing strong adoption in smaller cities including Indore, Ahmedabad, Coimbatore and Udaipur. The report pegs India’s broader retail market at a path to $1.5 trillion by 2030, growing at a 9–10 percent CAGR through FY30, with digital-first brands still capturing only a modest share of that pie — meaning the runway for non-metro D2C growth is, on paper, still early.

Some of this is simple infrastructure catching up. Return-to-origin rates on D2C orders — long a tax on smaller-city expansion because of cash-on-delivery risk and address-verification issues — fell from nearly 39 percent in the November 2025 festive season to about 21 percent by February 2026, per logistics platform Shipway’s data. Smartphone penetration in Tier-2 cities has crossed 70 percent, and household incomes in these markets have grown by close to 40 percent since 2018 — the kind of purchasing-power shift that turns “aspirational” categories into everyday ones.

What it looks like on the ground

Data on MILLD, the high-protein atta brand founded by Sivaram Briyas and EaseMyTrip co-founder Prashant Pitti, tracks closely with the macro numbers. Nine months after its November 2025 launch, MILLD’s five largest metro markets contribute just 38 percent of total orders — the rest comes from cities such as Mohali, Nagpur, Dehradun, Bhopal, Raipur and Vadodara, several of which saw order volumes rise six to nine times between December 2025 and June 2026. Nearly half of MILLD’s transactions now come from repeat customers, suggesting the smaller-city demand isn’t a one-time discovery spike but a sustained buying pattern.

That kind of trajectory complicates an old assumption in Indian D2C: that a functional nutrition brand needs a metro, gym-going audience before it can scale. MILLD’s growth suggests the opposite — that protein-forward, health-positioned products can find their fastest adopters in cities with no legacy “fitness culture” marketing to compete against.

Founders are already rewriting the playbook

The shift is starting to reshape how brands plan distribution and marketing from day one, rather than treating non-metro markets as a later-stage expansion. Regional-language content, local logistics partnerships and community-first trust-building — as opposed to paid performance marketing calibrated for metro CACs — are increasingly built into launch plans rather than bolted on afterward. Over 70 percent of India’s internet users consume content in regional languages, a data point that’s pushing D2C marketing teams to treat English-first Instagram campaigns as a metro-only tool rather than a default.

There’s a second, quieter shift buried in the SGA PR findings: consumers in these markets are described as moving beyond celebrity-led branding toward ingredient-conscious, outcome-driven purchase decisions. That sits in some tension with brands like MILLD leaning on a celebrity ambassador (Milind Soman) to drive awareness — a reminder that a well-matched ambassador can still open a market, but retention in Tier-2/3 India increasingly depends on product substance holding up once the initial curiosity wears off.

The road ahead

None of this means metro markets are becoming irrelevant — they remain the highest-value customers by average order size for most categories. But the growth curve has clearly shifted. For founders raising their next round, or currently deciding where to spend their first performance-marketing rupee, the numbers point to a straightforward conclusion: the brand that wins Bhopal in 2026 may be building something just as durable as the one that once won Bandra.

FAQs

What share of India’s D2C growth now comes from Tier-2 and Tier-3 cities?

Tier-2 and Tier-3 markets accounted for roughly 66 percent of new D2C orders and about 60 percent of incremental GMV in FY26, according to Unicommerce’s analysis of over 400 million order items.

How big is India’s D2C market expected to become?

Industry estimates put the current market at $10–12 billion, with projections of roughly $60 billion by 2030 as digital adoption and non-metro demand continue to widen.

Which categories are seeing the strongest Tier-2/3 adoption?

Protein nutrition, premium skincare and wellness supplements — categories once considered metro-only — are showing strong uptake in cities like Indore, Ahmedabad, Coimbatore and Udaipur.

Is celebrity endorsement still effective in these markets?

It still drives initial awareness, but industry data suggests Tier-2/3 consumers are increasingly ingredient-conscious and outcome-driven, meaning product substance matters more for retention than star power alone.

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ⓘ Editor’s note: LAFFAZ covers Camilla Araujo’s exit from OnlyFans as a creator-economy business story — specifically what happened next, when she turned her personal brand into a paid mentorship product. This piece does not link to or describe explicit content; all facts are drawn from her own public statements and named on-record sources.

Camilla Araujo announced she was leaving OnlyFans on Instagram on December 22, 2025, then formalized the exit on New Year’s Day with a nearly 15-minute YouTube documentary titled “Becoming Her” that passed 600,000 views within 24 hours. In it, Araujo said she’d built the account into 30 million followers and over $20 million in earnings across three years, then walked away from it at the peak.

The documentary leaned hard into her immigrant-family backstory — Brazilian parents, a one-bedroom apartment shared by four people, and a childhood built around getting her into college. She’s said the earnings let her help her parents retire and buy a home. Before OnlyFans, she’d already had one moment of mainstream visibility: appearing as “Player 067” in a MrBeast Squid Game recreation video.

“Over the last three years, I’ve gained over 30 million followers and made over $20 million. And yeah, mostly through OnlyFans. But today, I quit. But the reason probably isn’t what you think,” said Araujo in the video documentary

“I didn’t leave OnlyFans out of regret. I left because I grew.” she added

The Pivot: From Creator to Course-Seller

The same week as the documentary, Araujo opened applications for Becoming Her, a paid social-media mentorship program at BecomingHer.co, which she described as teaching the “Viral Content Formula” behind her earnings. She claimed over 50,000 people applied on launch night alone.

That’s a familiar move in the creator economy — a personal brand converting audience trust into a paid education product — but the pricing structure is what triggered scrutiny. According to reporting on the application funnel, applicants are asked how much they’re willing to invest, ranging from roughly $1,000 to $4,500; choosing under $2,500 routes them to a $67 self-guided guide, while anything above that threshold triggers a follow-up sales call. Other reports put the top tier as high as $8,000.

The Backlash

Fellow creator Forrest Smith went through the application process publicly and posted her findings on TikTok, calling out the program’s “interview” framing as a pressure tactic:

“That’s just a strategy to make you feel special so you’re more willing to spend $2K to $5K on a course.” — Forrest Smith, via TikTok

Smith and other users also flagged that the application asked for sensitive financial details — including credit score and weekly income — before granting access to pricing, and that the “limited spots” scarcity messaging didn’t hold up to scrutiny. Some commenters went further, calling the structure a “pay in pyramid scheme.” Araujo and her team have not publicly responded to the scam allegations; outlets including People confirmed they’d reached out for comment without response as of publication.

Why This Matters Beyond One Creator

Araujo’s situation is a clean case study in a pattern that’s becoming common across the creator economy: platform-native income is volatile and reputationally risky, so successful creators increasingly try to convert their audience into a second, more “legitimate”-looking business — coaching, courses, agencies. The tension is that the sales mechanics of that second business (application funnels, urgency messaging, tiered pricing gated behind income disclosure) are borrowed directly from high-ticket info-product marketing, a category with its own long history of predatory-practice complaints. Whether Becoming Her holds up as a real business or fades under the scrutiny will likely say more about that broader shift than about Araujo individually.

Camilla Araujo FAQ

How much did Camilla Araujo earn on OnlyFans?

She said in her documentary that she earned over $20 million across three years, mostly through OnlyFans, while building a following of over 30 million.

What is Camilla Araujo’s Becoming Her course?

It’s a paid social-media mentorship program launched January 1, 2026, priced between roughly $1,000 and $8,000 depending on the tier, teaching content-growth strategy.

Why is Becoming Her facing scam accusations?

Critics, including fellow creator Forrest Smith, have pointed to high-pressure sales tactics, requests for applicants’ credit scores and income, and content they say is available for free elsewhere.

Has Camilla Araujo responded to the backlash?

Not publicly in detail as of this writing; multiple outlets reported reaching out for comment without a response.

Conclusion

The documentary got the attention. The course is what will decide whether this becomes a genuine second act or a cautionary tale about monetizing an audience’s trust twice.

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Smallest.ai, the Bengaluru-based voice AI company, has raised $13 million in a Series A round led by Seligman Ventures, with participation from existing backers Sierra Ventures and 3one4 Capital, alongside Better Capital, Upsparks Capital, Schema Ventures, Tiny VC, DeVC and Mission Street Capital. The round takes the company’s total funding past $21 million.

Voice AI is one of the more crowded corners of enterprise AI right now, and Smallest.ai is a minnow next to the category’s better-funded names — rival ElevenLabs raised $500 million in February alone, and Fish Audio recently pulled in $52 million for its open-source speech platform. What Smallest.ai is selling instead is architecture: a real-time speech-to-speech system built to process listening, reasoning and response in parallel rather than waiting for a full audio clip before generating a reply, aimed at cutting the latency that makes AI voice agents sound robotic on calls with financial services, healthcare and contact-centre customers.

Founded by IIT Guwahati graduates Sudarshan Kamath (CEO) and Akshat Mandloi (CTO), Smallest.ai raised an $8 million seed round in October 2025 led by Sierra Ventures to build its low-latency Lightning algorithm and 4-billion-parameter Electron v2 model. A May hardware partnership with Tenstorrent claimed the ability to run 550 simultaneous voice calls for roughly $27,000 on 27 P100 accelerators, versus close to $100,000 on 11 NVIDIA L40S GPUs for comparable throughput — a cost argument the company is leaning on hard as it courts regulated industries where call volumes are high and margins on automation are thin.

Also Read: River Mobility raises $120 Mn Series C led by Elev8, Claypond

“Voice AI has gone through three generations of innovation, but each generation has ultimately hit the same wall. The industry has focused on making models larger when the real challenge is architectural. Humans don’t wait for someone to finish speaking before they begin thinking. We listen, think, and respond simultaneously. Voice AI needs to work the same way. That’s why we built Smallest.ai around a real-time architecture that processes speech as it arrives, enabling faster, more natural conversations without sacrificing intelligence. By rethinking the stack instead of simply scaling models, we’re reducing latency to the point where voice interactions feel genuinely human.” said Sudarshan Kamath, founder and CEO of Smallest.ai

The company, which currently employs close to 60 people, plans to use the fresh capital for product development, hiring and commercial expansion across financial services, healthcare, contact centres and business process outsourcing. With less than 1% of global voice interactions currently AI-powered, against a market industry forecasts expect to grow from $2.4 billion in 2024 to $47.5 billion by 2034, Smallest.ai’s bet is that architecture and cost efficiency can carve out enterprise share even against rivals with far deeper war chests.

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Vaaree, the Bengaluru-based home décor and furnishings marketplace, has raised ₹65 crore (around $6.6 million) in a Series A round led by Hero Enterprise, the investment arm of the Hero Group, and Cap Alpha Ventures (formerly Client Associates Alternate Fund), with existing backers Peak XV’s Surge, PeerCapital, All In Capital, Better Capital, OTP Ventures and entrepreneur Kunal Shah also participating.

India’s online home décor category has long struggled with a discovery problem rather than a supply one — the products exist, but buyers rarely trust how something will actually look in their own space until it arrives. Vaaree’s answer is VibeCheck, an AI-powered discovery layer that lets shoppers build moodboards, visualise product combinations and shop curated looks rather than browsing a flat product catalogue. The fresh capital will go toward expanding VibeCheck alongside fulfilment and quality-verification centres, part of a push toward next-day delivery in major Indian cities.

Founded in 2022 by Varun Vohra, Garima Luthra and Pranav Arora, Vaaree runs a curated marketplace of more than 1.5 lakh products spanning décor, furnishings, bed and bath, kitchen and lighting, working with a selective slice of manufacturers that meet its quality and design standards rather than listing everything available. The round follows a $4.6 million pre-Series A last year and an earlier $4 million seed led by Peak XV’s Surge, giving the company a fairly conventional early-stage trajectory before this larger institutional round brought in a strategic name in Hero Enterprise.

Also Read: HomeRun raises $12 Mn Series A+ led by Nexus Venture Partners

“The problem in home category is not a lack of products. It is the lack of confidence customers feel while putting a space together. Most people know how they want their home to feel but translating that into the right products is difficult. With VibeCheck, we want to give every Indian access to a personal home stylist, one that understands their taste, helps them visualize complete spaces and makes every recommendation instantly shoppable. This funding allows us to strengthen both sides of that experience: technology that makes home styling simpler and fulfilment infrastructure that gets those products to customers faster,” said Varun Vohra, Co-founder, Vaaree.

Hero Enterprise’s involvement adds a manufacturing and consumer-brand pedigree to the cap table that pure financial investors don’t bring, and Munjal’s own framing of the deal — betting on Vaaree’s supply chain and quality-assurance discipline as much as its AI layer — suggests the round is as much about operational credibility as capital. For a category where trust in what arrives at the door has historically been the biggest drag on conversion, that combination of AI-led discovery and a strategic investor focused on supply chain rigour is a reasonably specific bet on where the next round of growth in Indian home décor e-commerce will come from.

“Vaaree is addressing a large and highly fragmented market with a differentiated, technology-led platform. The company has built a world-class supply chain and a robust quality assurance framework, while leveraging technology to curate its product assortment, personalize the customer experience, and simplify what is often an overwhelming home styling journey,” said Sunil Kant Munjal, Chairman, Hero Enterprise.

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Arboreal Bioinnovations, a Lucknow-based specialty food and nutraceutical ingredients company, has raised ₹230 crore (over $24 million) in a Series A round co-led by EAAA Alternatives, the alternatives investment arm of Edelweiss, and agrifood-focused Omnivore, with existing investor Rainmatter by Zerodha also participating.

The size of the round stands out in a segment that rarely sees Series A cheques this large. India’s specialty ingredients industry has quietly become one of the more capital-intensive corners of the food-tech ecosystem, as consumer packaged goods companies push suppliers to deliver science-backed alternatives — sugar-reduction systems, alternative proteins, cocoa-based ingredients — fast enough to keep pace with shifting nutrition labels and health-conscious demand. Building that kind of ingredient engineering and precision manufacturing capability upfront costs more than a typical software or D2C Series A, which is part of why investors are willing to write outsized early checks into companies that can prove out the science.

Founded in 2018 by Swati Pandey and Manish Chauhan, Arboreal runs an integrated platform spanning ingredient engineering, process R&D, formulation science and precision manufacturing, and says it has supported more than 300 product launches for over 1,100 B2B customers across food, beverage and nutraceutical categories. The Series A is also the first investment out of EAAA’s second Discovery Fund, which closed above ₹1,200 crore — meaning Arboreal effectively became the debut bet for a freshly capitalised pool of money specifically built to back category-defining businesses.

Also Read: Mitti Labs raises $9.5 Mn Series A led by Aramco Ventures

“This fundraise is a strong validation of the direction we are taking as a company. It gives us the fuel to accelerate our mission of building clean, science-led solutions that address some of the world’s most pressing nutritional and food challenges, with innovation originating in India and reaching consumers globally.” said Swati Pandey, Co-founder & CEO, Arboreal Bioinnovations

The company plans to direct the capital toward expanding manufacturing capacity, deepening R&D, and speeding up commercialisation of its next generation of functional ingredients. For a Discovery Fund built to find and back category leaders early, Arboreal’s ability to already claim 1,100 customers and 300 product launches likely mattered more than the ticket size — it suggests the science has cleared commercial validation, leaving capital as the remaining constraint on scale.

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River Mobility, the Bengaluru-based electric two-wheeler manufacturer, has raised $120 million in a Series C round comprising equity and venture debt, one of the largest private funding rounds yet in India’s electric two-wheeler segment. The equity portion was led by Elev8 Venture Partners and Claypond Capital, with participation from Singularity AMC, Anicut Capital, 360 ONE Asset, JIF Capital and HDFC AMC, while existing global backers Yamaha Motor Corporation, Al Futtaim Group and Mitsui & Co also returned. Alteria Capital, InnoVen Capital and Stride Ventures joined through venture debt.

The round is notable less for its size than for whose money is in it. Since its Series A, River had raised almost entirely from global names — Yamaha, Marubeni, Mitsui, Al Futtaim, Lowercarbon Capital, Toyota Ventures, Maniv Mobility — a foreign-capital-heavy cap table that is fairly unusual for an Indian EV manufacturer at this stage. This Series C marks River’s first significant backing from Indian institutional investors, a shift that suggests domestic capital is now willing to underwrite electric two-wheeler manufacturing at scale rather than leaving that risk to strategic automotive investors and international climate funds.

Founded in March 2021 by Aravind Mani and Vipin George, River has built its business around a single flagship model, the utility-focused electric scooter Indie, launched in 2023, rather than spreading across a wide product range early. The company raised $15 million in its Series A in June 2023 and $40 million in a Series B led by Yamaha in February 2024, giving it a fairly conventional funding cadence before this considerably larger Series C. Founder and CEO Aravind Mani told TechCrunch that less than 10-12% of the round was venture debt and that the equity portion was entirely primary capital, with no secondary share sales — a detail that matters because it means existing shareholders aren’t cashing out, and all $120 million is going into the company rather than partly to early investors exiting.

“This funding marks an important milestone in River’s journey. The confidence shown by both our existing and new investors reinforces our belief that there is tremendous opportunity to build India’s first utility and design based mobility brand,” said Aravind Mani, co-founder and CEO of River Mobility

The fresh capital will fund capacity expansion at River’s existing manufacturing facility, a new greenfield plant, new products in the utility lifestyle segment, and a push toward gross margin expansion and EBITDA profitability — the last two signalling that River, like most of India’s EV two-wheeler makers, is still working toward unit-level profitability rather than having already reached it. With India’s electric two-wheeler market moving past early adoption into what investors are now calling a defining growth phase, River’s bet is that a single well-executed model and vertically integrated manufacturing can hold ground against rivals selling across far broader product lines.

“The electric two-wheeler market in India is entering a defining growth phase, driven by strong consumer adoption, improving economics, and increasing demand for differentiated products. River stands out for its sharp product thinking, exceptional execution capability, and a highly differentiated positioning in the market. Aravind, Vipin and the team have built a brand that resonates deeply with consumers looking for brilliant design, utility and durability. We believe River is well-positioned to emerge as one of the defining EV companies from India.” said Navin Honagudi, Managing Partner, Elev8 Venture Partners

“River has combined disciplined execution and thoughtful product differentiation to rapidly grow and garner customer love in a competitive market. We are excited to support the team as they scale further while contributing to the country’s energy transition and domestic manufacturing ambitions.” said Sekhar Garisa, Managing Director, Claypond Capital

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HomeRun, the Bengaluru-based quick commerce startup for construction and interior materials, has raised $12 million in a Series A+ round led by Nexus Venture Partners, with existing backers Sorin Investments, Titan Capital, Sparrow Capital and Consumer Collective by Atrium also participating. The company has not disclosed its post-money valuation or the dilution the round represents.

The pace of HomeRun’s fundraising says almost as much as the round itself. This is the company’s third priced round in roughly nine months — a ₹9 crore seed in November 2025, a ₹60 crore ($6.6 million) Series A led by Sorin Investments in February 2026, and now this Series A+ — taking its total disclosed capital to around $19.6 million against an operating footprint that, as of its last public snapshot, was still confined to five dark stores in a single city. That capital-to-footprint gap is the central bet Nexus is underwriting: that construction materials, a category still dominated by fragmented neighbourhood hardware stores and cement-brand exclusive dealers, can be pulled onto a hyperlocal delivery model the way groceries and pharmacy already have been, and that HomeRun can prove that quickly enough to justify raising this far ahead of its city count.

Founded by Pukhraj Singh Grewal, who previously ran construction-labour marketplace Project Hero before winding it down and pivoting into materials delivery in December 2024, HomeRun promises 60-90 minute delivery of cement, tiles, plywood, wires and paints across roughly 105 pincodes in Bengaluru, sourced through authorised dealers with an all-electric delivery fleet. The company has reported an average order value of around ₹7,000 and more than 100,000 fulfilled orders to date, alongside a claimed 8X growth over the past year — though it has not specified whether that growth figure refers to orders, gross merchandise value or revenue.

Unlike grocery quick commerce, where a single delivery might weigh a few kilograms, HomeRun’s per-order logistics carry cement bags, plywood boards and bulk wire spools — cargo that is structurally heavier and costlier to move, which means the reported average order value alone doesn’t confirm the unit economics are contribution-positive once dark-store rent and inventory holding are factored in. The fresh capital is earmarked for entering new cities beyond Bengaluru, deepening the supply chain, and expanding the product catalogue, with Hyderabad and Pune flagged as likely next markets. The category is filling in fast: rival Fixxly closed a $5.5 million seed from Accel, Fireside Ventures and Lightspeed India Partners in late July with a September launch planned, while established B2B platforms Infra.Market and JSW One MSME already hold considerably deeper balance sheets in adjacent segments.

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Mitti Labs, a climate-tech company headquartered in New York with operations run out of Bengaluru, has raised $9.5 million in a Series A round led by Aramco Ventures, the venture arm of Saudi Aramco, marking the fund’s first investment in India. Returning investor Lightspeed India was joined by first-time backers Godrej Industries Group, Cisco Foundation, Francis Family Fund and Volta Circle, taking Mitti Labs’ total raised to $12.5 million.

The round is a fairly specific bet on where climate-tech capital is heading next. Rice covers roughly a fifth of Asia’s cultivated land, consumes more than 30% of the world’s irrigation water, and is one of agriculture’s largest single sources of methane because of how continuously flooded paddies work — yet the vast majority of that farming happens on fragmented plots under two hectares, where reliable data on water use, yields and emissions has historically not existed at all. Mitti Labs’ pitch is that satellite radar and AI can generate that missing data at the level of an individual field rather than an entire region, turning what used to be an unmeasurable problem into one large companies can actually underwrite and pay to fix.

Founded in 2023 by Xavier Laguarta Soler, Devdut Dalal and Nate Torbick, Mitti Labs runs a GeoAI platform, developed with NASA support, that fuses high-resolution synthetic aperture radar imagery with years of field-collected ground truth to build digital twins of individual rice plots — tracking soil moisture, flooding and crop health remotely across smallholder farms that have never had this kind of monitoring before. The company says its programs have grown from around 8,000 participating farmers in their 2024 debut season to more than 100,000 across several Indian states today, and that the water-saving irrigation techniques it promotes, primarily alternate wetting and drying, can cut water consumption by roughly 40% and methane emissions by more than half without reducing yields. Clients already paying for that data include carbon marketplace Cool Effect, rice producer Ebro Foods and agrochemical company Syngenta.

“Rice covers a fifth of Asia’s cultivated land, and it is both a major source of methane and one of the most water-intensive crops grown. Changing farming practices is not easy, but the harder part has been knowing what is actually happening in the fields across millions of small farms. That is what Mitti Labs’ AI and satellite technology aims to solve.” said Zayed AlAmri, Executive Managing Director of Aramco Ventures

“Solving the world’s water crisis requires bringing together smallholder farmers, industry stakeholders, governments, and nonprofits to transform how rice is grown. With its unique technology and vast network of farmer-partners, Mitti Labs can unlock new revenue opportunities tied to this transition and help build the future of rice,” said Hemant Mohapatra, Partner at Lightspeed India.

“As an investor deeply rooted in India, we know firsthand how critical water resilience is for farming communities. Mitti Labs has built a remarkable model that leverages technology towards securing the livelihoods of smallholder farmers. This model has the potential to reshape rice farming all over Asia,” said Burjis Godrej, Chairperson of Godrej Agrovet

With the fresh capital, Mitti Labs plans to deepen its footprint across India while launching greenfield projects in the Philippines later this year, followed by Indonesia and other Southeast Asian markets in 2027 — expansion that would let it serve compliance carbon markets, where emissions cuts are legally mandated, alongside the voluntary market it currently operates in. For an oil major’s venture arm, backing a methane-measurement startup working India’s rice belt is a comparatively small cheque, but it signals that water and emissions accounting in agriculture has become a cost line serious enough for energy companies to want a stake in the tools that measure it.

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Smart buildings are transforming the way businesses operate. According to Fortune Business Insights, the global smart buildings market is expected to grow from over $120 billion in 2024 to more than $300 billion by 2032, driven by demand for automation, energy efficiency, and connected technologies. At the same time, commercial properties continue to face growing security risks. The FBI reported more than 847,000 burglary offenses in the United States in its latest crime statistics, while insider threats, unauthorized access, and after-hours incidents remain common concerns for offices, warehouses, healthcare facilities, and corporate campuses.

Modern commercial buildings are no longer just physical spaces. They are connected ecosystems filled with employees, visitors, sensitive business data, expensive equipment, and critical infrastructure. Traditional cameras that simply record footage are no longer enough because they only help after an incident has already occurred.

This is where AI-powered commercial security systems are changing the game. A 2025 security trends survey from ASIS International, the leading nonprofit association for security professionals, found that among security teams already using AI, roughly a third reported it helped automate incident response and expand perimeter-monitoring capacity, freeing frontline staff from routine patrolling. By combining intelligent video analytics, access control, and automated alerts, businesses can identify threats in real time, respond faster, and improve operational efficiency.

In this article, you’ll learn why AI-powered security is becoming essential for smart commercial buildings, the biggest benefits it offers, and how businesses are using it to create safer and more efficient workplaces.

1. Smart Buildings Need Security That Can Think in Real Time

A modern commercial building can generate thousands of security events every day. Employees badge into offices, visitors arrive throughout the day, deliveries are made, contractors access restricted areas, and cleaning staff work after hours. Monitoring all of these activities manually is nearly impossible.

AI changes this by continuously analyzing live video instead of simply recording it. Rather than waiting for someone to review footage after an incident, AI identifies unusual behaviour as it happens.

For example, AI can detect:

• Someone entering a restricted area.
• A person remaining in a sensitive location longer than expected.
• Movement inside a building after business hours.
• Unauthorized access attempts.

This allows security teams to respond within minutes instead of discovering problems hours later.

A good example is Coram’s commercial security systems, which combine AI-powered video surveillance, cloud-based access control, emergency response, and centralized management into a single platform. Instead of replacing existing infrastructure, the platform integrates cameras, access events, and alerts into one dashboard, helping organizations monitor multiple commercial sites while automatically detecting incidents such as forced entry, tailgating, or after-hours access.

2. Faster Threat Detection Reduces Business Risk

Time is one of the biggest factors during a security incident.

Whether someone forces open a door, enters a server room without authorization, or attempts to steal equipment, every minute matters.

Traditional systems usually require security staff to notice the problem first. AI continuously monitors every connected camera and instantly sends alerts when suspicious activity matches predefined conditions.

For example, instead of reviewing several hours of surveillance footage after an incident, security teams receive immediate notifications with video evidence attached.

This faster response helps businesses:

• Prevent theft before it escalates
• Reduce property damage
• Improve employee safety
• Minimize operational disruptions

For large office buildings, manufacturing facilities, and corporate campuses, these few minutes can prevent significant financial losses.

3. AI Makes Access Control Much Smarter

Controlling who enters a commercial building has become increasingly difficult.

Modern organizations manage employees, contractors, visitors, delivery personnel, maintenance workers, and temporary staff, each requiring different access permissions.

AI-powered systems add intelligence to traditional access control by connecting entry events with video verification.

Instead of simply recording that a badge was used, security teams can immediately see:

• Who entered
• When they entered
• Whether someone followed behind without authorization
• What happened immediately after access was granted

This creates a much stronger security process while reducing manual investigations.

For organizations operating across multiple buildings, centralized access management also makes it easier to update permissions, remove inactive credentials, and maintain consistent security policies.

4. AI Reduces the Workload for Security Teams

Many commercial properties continue to expand while security departments remain relatively small.

Monitoring dozens or even hundreds of cameras for an entire shift is both difficult and exhausting. Human attention naturally declines after long periods of repetitive monitoring.

AI helps by filtering out routine activity and highlighting only events that actually require attention.

Instead of watching live video continuously, security teams focus only on meaningful alerts such as:

• Forced entry attempts
• Unauthorized access
• Loitering in restricted areas
• Suspicious movement after business hours

This not only improves response times but also allows existing staff to manage much larger facilities without significantly increasing operating costs.

5. Commercial Security Is Now About Business Intelligence

Modern AI systems do more than improve physical security.

They also generate operational insights that help businesses improve efficiency.

For example, organizations can understand:

• Which entrances experience the highest traffic
• Peak visitor hours
• Areas with frequent unauthorized access attempts
• Employee movement patterns
• Facility usage across different times of the day

These insights help facility managers optimize staffing, improve visitor management, adjust building operations, and identify potential bottlenecks.

Instead of security data remaining isolated, it becomes valuable information that supports better business decisions.

6. AI Helps Commercial Buildings Scale More Easily

As organizations grow, their security requirements become much more complex.

Opening new offices traditionally meant purchasing additional hardware, configuring multiple systems, and managing each location independently.

Cloud-based AI platforms simplify expansion by allowing administrators to manage multiple sites from one dashboard.

Whether a company operates:

• Five offices
• Twenty retail locations
• Multiple warehouses
• National corporate campuses

Administrators can apply consistent security policies, manage user permissions, monitor live events, and investigate incidents from a centralized interface.

This makes scaling significantly easier while maintaining consistent protection across every location.

7. AI Improves Emergency Response

Security incidents rarely happen in isolation.

A single event may require security teams, building managers, emergency responders, and executives to coordinate quickly.

AI-powered commercial security systems help automate this process.

Instead of relying on manual communication, modern systems can immediately:

• Trigger security alerts
• Lock sensitive areas
• Share live video with authorized personnel
• Record every access event
• Provide real-time visibility during emergencies

This coordinated response reduces confusion during critical situations and allows businesses to protect employees while minimizing disruption to operations.

Key Takeaways

• Smart buildings require proactive security instead of passive surveillance.
• AI detects suspicious behaviour in real time instead of relying on manual monitoring.
• Intelligent access control improves both security and accountability.
• AI reduces investigation time while helping security teams focus on genuine threats.
• Commercial security data can also improve operational efficiency and business decision-making.
• Cloud-based platforms simplify security management across multiple buildings.
• Automated emergency response helps organizations react faster during critical incidents.

Frequently Asked Questions

What are commercial security systems?

Commercial security systems are integrated technologies that help businesses protect buildings, employees, visitors, and assets. They typically include surveillance cameras, access control, alarms, and increasingly, AI-powered analytics for real-time threat detection.

Why are AI-powered commercial security systems better than traditional CCTV?

Traditional CCTV primarily records footage for later review. AI-powered systems actively analyze live video, detect unusual behaviour, send instant alerts, and automate security responses, allowing businesses to prevent incidents rather than simply investigate them afterward.

Can AI security systems work with existing cameras?

Many modern AI security platforms are designed to integrate with existing IP camera infrastructure, reducing the need for expensive hardware replacements while adding advanced analytics and automation capabilities.

Which businesses benefit the most from AI commercial security systems?

Office buildings, healthcare facilities, warehouses, manufacturing plants, retail stores, corporate campuses, logistics centers, and mixed-use commercial properties can all benefit from AI-powered security because they manage large numbers of people, assets, and access points.

Conclusion

As commercial buildings become smarter, security must evolve alongside them. Businesses can no longer rely on systems that simply record events after they happen. AI-powered commercial security systems provide real-time visibility, intelligent automation, faster incident response, and better operational insights, making them a valuable investment for organizations of every size. Properties with sophisticated, AI-driven security and building intelligence now command rental rates 8 to 12% higher than comparable properties still relying on traditional approaches, according to recent real estate industry data.

The question is no longer whether smart buildings should adopt AI-powered security. The real question is how long businesses can afford to operate without it.

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“You only have to do a very few things right in your life so long as you don’t do too many things wrong.” — Warren Buffett

I was recently invited as a Keynote Speaker for the DTU E-Summit ’26 at Delhi Technological University (Formerly Delhi College of Engineering), India.

The Speaker session was well put together by the E-Cell DTU Team, and the team and the audience queried on varied topics such as, including but not limited to, what differentiates startup ideas that remain ideas from those that become real companies, balancing growth with financial discipline and runway management, when not to fundraise during your startup journey, the skills every entrepreneur should master, and more.

The recorded session is shared below, as also some of the ideas are shared right after.

Though questions were taken up on varied topics, we will address when not to fundraise during one’s startup journey in this post.

A venture should ideally not raise Venture Capital (VC) when the business is not naturally suited to the VC model; some examples of the same being that the venture has not yet proven it’s basic product-market fit, it cannot credibly scale into a very large outcome, or the capital would mainly be used to survive/figure some of the basic things out rather than accelerate a clear growth engine. In practice, VC is a good fit and works best only when speed, scale, and a venture-sized exit are probable; otherwise, the dilution, board control, and pressure to grow fast can hurt the venture more than help it.

When Not to Raise Venture Capital

I. There are no clear indicators about the road to Product-Market Fit (PMF)

If customers are not consistently using, retaining, and paying for the product, VC money often ends up just funding more experimentation, instead of scaling something that already works. Accelerating or even maintaining the growth rate, vis-à-vis managing early numbers and traction, is easier said than done.

Cases where the ventures might still be able to make a solid case for VC pre-basic PMF include deep-tech, biotech, or platform-shift companies that must raise capital before, because the product itself requires heavy R&D or long timelines. In those cases, investors are considering and betting on future trends, the current pace of technological progress, and future market behaviour and timing.

II. The cap table is broken or too messy

If founders own too little, prior investors own too much, or there is dead equity and no clear governance, institutional investors may consider the round as hard to close or structurally difficult. Having politically, judicially, or bureaucratically affiliated leaders with significant equity on your cap table might also have less desirable effects on your fundraising efforts at the earliest stages. Needless to say, there should also be no significant equity for anyone, especially co-founders or core team members, with questions on their integrity in the past (everything will come up in due diligence).

Ideally, before your very first institutional fundraise happens, the founders and the founding team working full-time for the company should still have at least 70 – 80% of the company equity with them, so that even with succeeding fundraising rounds as everyone gets diluted, there is still enough incentive to carry on and take the results to the finish line, vis-à-vis generating returns, and/or exits, to the investors.

To redeem a broken cap table, one will have to fix this through rebalancing ownership, removing dead equity, or restructuring governance. Easier said than done, but harder to fundraise till this happens.

III. The market is too small or too slow, and the margins are razor-thin in a crowded market

After securing venture capital, most businesses invest in growth while improving unit economics over time. Given how much time, capital, and energy are required to translate into a massive outcome, chances are that low-margin, highly competitive businesses in a crowded or saturated market can end up burning cash without ever creating the venture capital-sized scale returns required for the investment to be considered successful. A solid business can still be a bad VC-Business fit if it is unlikely to reach the scale VCs need for their return profile within their fund cycle.

As Don Valentine would say, “Target Big Markets: If you don’t attack a big market, it’s highly unlikely you are ever going to build a big company.”

Do note that in cases where ventures are disrupting the current business landscape and creating a platform shift altogether, even though they might have thin unit economics early on in a market that is huge enough, the ventures can still improve upon and create some dominance or moat with volume, network effects, or infrastructure advantages. In such cases, a startup can make a credible case for venture capital if it has strong retention, a clear wedge, and a credible path to a large outcome, and where venture capital might work out for the stakeholders involved, including, and especially for, the investors. Two examples would be Reliance Jio in India and WhatsApp globally.

IV. Lack of focus on, or within, a single business

If you are a first-time founder managing 5+ different businesses at the same time, chances are that you are sacrificing your focus and the potential success outcome a fair bit.

Many eons back, I was part of the founding team with a friend who is a Marquis Who’s Who serial entrepreneur & global innovator (we were at least a decade early to the market, if not more), and we were planning to get into multiple sectors with customized innovative hardware-software offerings at scale for those sectors. I remember catching up with my good friend Yinglan, for whom I have the highest regard and respect, who shared with me that “At the earliest stages, if you focus even on ‘just two’ entirely different things, you might end up focussing on none.”

It’s one of those timeless pieces of advice that still holds.

It is tough enough to build a single venture (90% of the startups fail), and if the founders do not come across as wholly committed to going all out for a single venture and the outcome, it is only fair not to expect institutional investors to commit their capital to a single venture outcome, from amongst the multiple ventures where the focus might be getting divided.

Over time, as one gains more understanding of high-quality teams, putting in place the right incentives, management systems, processes, distribution, the domino effect, etc., one might be able to manage more than one business at a time. We will always have outliers like Elon Musk, Jack Dorsey, and Brad Jacobs, amongst other good business leaders; but managing multiple businesses without the right foundation and frameworks first built in works less for most people than we might assume.

At the end of the day, one needs to take into account that the leaders in venture capital firms are also operating their own businesses, with returns to be generated for their Limited Partners (LPs) within their committed fund cycles. If the investment does not look like it can generate the kind of returns within the specified time period, more often than not, the venture is just not a fit for their investment thesis.

More often than not, one’s venture might not necessarily need a huge amount of capital to be invested at the starting line itself. If a company can reach profitability or meaningful scale (and if that happens to be the goal) with modest funding, venture capital might not really be required.

Also, given there are always exceptions, if you happen to be a serial entrepreneur with an exit track-record, or if you are a first-time high-quality founding team with integrity, who has this crazy vision about the future, and the execution chops to disrupt the status quo and make things happen, for all you know, despite all the odds and all the investment theses, you might still luck out and either still raise the funding, or make it to someone’s anti-portfolio.

Keep refining, keep building!

*Delhi Technological University (DTU), formerly Delhi College of Engineering (DCE), is amongst the leading technology institutions in India.

ⓘ The above article was originally published by Monce C. Abraham on his official portal.

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Pursue what catches your heart, not what catches your eyes. – Roy T. Bennett

A few years back, I was invited to be one of the Esteemed Speakers for the NSUT E-Summit ’20 at the Netaji Subhas University of Technology (NSUT), India.

The Speaker session was well put together by the E-Cell NSUT Team, and the audience queried on varied topics such as, including but not limited to, whether every student needs to start a startup and where one finds the motivation to do so, prepping up to be an entrepreneur, building a diverse team and trying to raise funding from investors during the college years, and common reasons why startups fail.

The recorded session is shared below, as also some of the ideas are shared right after.

Though questions were taken up on varied topics, we will address whether every student needs to start a startup, and where one finds the motivation to do so.

Startups and The Pursuit of Entrepreneurship

I. There is no One Road to Success

Everyone is built differently, has different gifts and motivations, and their own journey to go through. What works for one might not necessarily work for others.

Not everyone needs to start a startup. In addition to choosing a goal that stretches you a bit (or more) beyond your current comfort zones, seeing the bigger picture and working for the longer term, hard and smart work, a bit of speed and timing, and a bit of luck, there is actually no playbook.

There is no ‘one road’ to success.

II. Entrepreneurship is not a job, it’s a lifestyle

As much as you would like to believe that the world of entrepreneurship is full of glamour and glory, the truth is, to make it work you will have to dive in head-on and work on it unlike anything you have ever been remotely passionate about.

Entrepreneurship seldom works part-time (9 AM – 5 PM, or, 7 PM to 2 AM) – once you have tested the waters and are convinced this is something you should be doing, there is only one way to go – diving right in. This means making the venture your full-time and all other initiatives part-time.

Wherever you go, whatever you do, you are always thinking of taking your venture to the next level and creating something worthwhile and good enough to be used outside your circle of immediate influence.

If you are not passionate enough to go the whole way, do yourself a favor, save yourself some heartache and misery… and don’t start up. If you love what you are getting into just enough to consider working on this the whole day, the whole week, and then the next 3 years (at least) without much hope of early signs of reward, go for it.

Keep your eyes and ears open, take feedback on your venture where you catch anything relevant, check with your gut feeling (this comes in quite handy when taking on tough decisions)… and keep on moving with what you know you have to do next.

Be ready to embrace rejection and disappointment too: You might be working super hard to make your vision come true and pulling out all stops, but sometimes things just aren’t meant to happen. Sometimes it’s the team, other times it’s the product-market fit, sometimes you might just run out of runway, and then again, sometimes the time for the idea might not have just come yet. Be prepared to see your life’s work burn before your eyes.

Remember you have chosen this path, and that you alone are responsible for all things that come with it. Get out of your comfort zone, expand your boundaries, and make things happen, and of course… enjoy whilst you are at it, you only have so little time.

The lack of motivation usually comes when you are pursuing someone else’s dream. Work on your dream, not on anyone else’s dream. – Monce C. Abraham

*Netaji Subhas University of Technology (NSUT) is amongst the leading technology institutions in India.

ⓘ The above article was originally published by Monce C. Abraham on his official portal.

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Former Indian cricket captain MS Dhoni has invested in residential rooftop solar startup SolarSquare through his family office, Midas Deals, as part of the company’s recently closed $53 million Series C funding round. Dhoni will also join SolarSquare as its brand ambassador.

Founded by Shreya Mishra and Nikhil Nahar, Gurugram-based SolarSquare provides end-to-end rooftop solar solutions spanning consultation, installation, financing, monitoring, and after-sales support. The company says it has installed rooftop solar systems in more than 50,000 homes across 29 cities.

The Series C itself was led by Lightspeed, with participation from Lowercarbon Capital, NGP Capital, Elevation Capital, and existing investors. Following the round, SolarSquare plans to expand into 30 to 40 new cities, strengthen its technology platform, widen financing options, and invest further in customer service infrastructure.

Dhoni’s entry follows a pattern that has become increasingly common in Indian consumer-tech investing, where celebrity backers are brought in less for capital and more for the trust and reach they carry with first-time buyers. For a category like residential solar, where adoption still depends heavily on convincing homeowners to make an unfamiliar, high-ticket purchase, a widely recognised name attached to the brand can shortcut some of that consumer hesitation in ways a venture capital signature cannot.

The fresh capital will be used to expand SolarSquare’s presence and accelerate the adoption of residential rooftop solar across India, a market that remains underpenetrated relative to the government’s renewable energy targets despite growing urban demand for lower electricity bills and cleaner power sources.

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Plazza, a Bengaluru-based pharmacy-first quick commerce startup, has raised $15 million in a Series A funding round co-led by Accel, Elevation Capital, and Nexus Venture Partners. Existing investors All In Capital and Better Capital also participated in the round.

The fresh capital will go toward strengthening Plazza’s technology platform, deepening its AI-driven inventory and assortment intelligence, building out operational capabilities, and expanding its pharmacy network into new geographies.

The round arrives roughly 10 months after Plazza, founded in 2024 by Aman Priyadarshi, raised $1.4 million in a seed round led by All In Capital, with participation from Better Capital, Tracxn founder Abhishek Goyal, Vivekananda Hallekere, the Singhania family office, and promoters of JK Tyre. That quick jump from seed to a $15 million Series A signals investors are betting on pharmacy-focused quick commerce as a distinct, defensible category rather than a feature bolted onto general grocery delivery.

Plazza operates on a model built around deep inventory rather than speed alone. According to the company, each Plazza store stocks more than 40,000 SKUs — around eight times the range of a typical neighbourhood pharmacy — enabling prescription fill rates the company claims exceed 95%, compared with an industry average of 50% to 60%. The company also claims its gross merchandise value grew nearly 27X between June 2025 and March 2026, with repeat customers placing baskets roughly 30% larger than first-time users.

The bet is on a real gap in India’s pharmaceutical retail market: neighbourhood pharmacies typically carry around 5,000 medicines even though the broader market spans more than 100,000 SKUs, leaving frequent stockouts for anything beyond common prescriptions.

Plazza is entering a segment that has rapidly gone from a niche bet to a contested battleground. Flipkart entered quick medicine delivery through Flipkart Minutes in December 2024, while Zepto launched its own pharmacy vertical in 2025, promising 10-minute delivery in select cities. Blinkit has pushed beyond over-the-counter medicines by piloting prescription delivery in Bengaluru. Standalone online pharmacy players have also drawn capital of their own — PlatinumRx raised $6 million led by Stellaris Venture Partners in September 2025, while Truemeds secured $85 million in a round led by Accel and Peak XV Partners.

With three of India’s most active early-stage investors now backing Plazza directly, the startup’s near-term challenge shifts from proving demand to defending margins as horizontal quick commerce platforms encroach on pharmacy as just another delivery category rather than a specialised one.

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Blockchain promises faster, verifiable, tamper-resistant settlement for currency trades — but the $9.6 trillion-a-day forex market still comes with real risks beginners need to weigh first.

Imagine a currency market where all transactions settle in a fraction of the typical time, are instantly verifiable, and are very difficult to tamper with. That’s what blockchain technology promises for forex.

Curious investors are asking the same question as digital ledgers subtly upend one of the oldest financial systems in the world: is this the future of currency trading, or is it just hype? Context matters here — the global foreign exchange market is already the largest financial market on the planet, with daily turnover hitting $9.6 trillion in April 2025, a 28% jump from 2022, according to the Bank for International Settlements’ Triennial Central Bank Survey. Any technology that can shave cost or time off a market that size draws attention fast.

This guide unpacks what forex trading blockchain actually involves, separating the substance from the hype before any money changes hands.

What Is Forex Trading Blockchain Technology?

So, forex trading blockchain is basically when you use decentralized ledger systems to execute, record, and verify currency trades. It’s not just centralized banks or brokers doing everything; blockchains let transactions get recorded across a distributed network of computers instead.

What does this mean? Every trade is transparent, traceable, and almost impossible to change after it happens. If you’re a beginner, just think of it like a shared digital notebook that everyone can see, but no single person actually controls.

Blockchain first appeared in 2009 as people mined the first block of Bitcoin. This evolved into other concepts such as peer-to-peer electronic cash systems. Today, blockchain is undoubtedly popular in forex trading and other forms of digital financial trading.

Why Blockchain Is Gaining Ground in Forex Markets

Normal forex trading usually has a lot of middlemen involved, and each one adds more time and more cost to the transaction. Blockchain cuts through all that. Since you’re removing the middlemen that aren’t really needed, trades can go through quicker and cheaper — some blockchain-based settlement systems now process cross-border transactions in seconds instead of the three-to-five business days typical of correspondent banking, and can cut remittance costs by as much as 80%.

This is a big part of why so many brokers and platforms are now looking into forex trading blockchain solutions; traders these days care a lot about cost. Additionally, it is a transparent concept where operations are decentralized.

Forex trading blockchain makes it possible to pool resources and provide high liquidity. And this is what new investors are looking for in any forex trading platform.

The Security Advantage of Forex Trading Blockchain

One of the big reasons people bring up blockchain when talking about forex is security. Transactions are encrypted and distributed across the network, which makes tampering with the records a genuinely difficult task for any single bad actor. In fact, the concept has been adopted by banks and other financial institutions because of its high security — SWIFT itself tested blockchain-based cross-border settlement with Ant International and HSBC in December 2025, a sign that legacy financial infrastructure is adapting rather than resisting the shift.

Every single trade leaves behind a trail that you can actually go back and check. And for beginners who are nervous about getting scammed or dealing with a shady broker, that’s a big deal; it gives you some peace of mind knowing there’s an extra layer of security protecting you.

Key Risks Every Beginner Should Understand

Okay, so forex trading blockchain sounds great, but it’s not all risk-free; there are downsides too. For one thing, the regulations surrounding blockchain are still developing. Different countries have different rules, and it’s honestly hard to keep track of.

Also, you’ve got to be careful with blockchain platforms because scams are out there, so definitely do your research before you invest any money. Only genuine and legit platforms can ensure transparency for traders. They make certain that all transactions are clean and done according to set regulations.

And don’t forget market volatility is a concern here too, just as with regular forex trading. Before you begin to trade, ensure that you understand how volatility affects forex trading and what you need to adapt.

How to Get Started with Forex Trading Blockchain Safely

If you want to try out forex trading blockchain platforms, don’t go all in at once; start small first. Try to pick brokers that are regulated and have been around a while and don’t ever put in money you can’t afford to lose; that’s a big one.

Moreover, you should spend some time learning how blockchain transactions actually work before you jump in, and if the platform has a demo account, use that to practice first. The good thing is that all legit platforms offer a lot of information to help you make informed decisions.

Regulations change a lot depending on where you live too, so keep an eye on regulations in your area. Honestly, the more you learn, the less likely you are to make an expensive mistake.

Where Beginners Go From Here

Blockchain is subtly changing the norms of currency trading by providing security, speed, and transparency that conventional systems find difficult to match. However, it necessitates prudence, investigation, and a will to continue learning, just like any new technology.

The potential for novices can be realized by building knowledge first rather than jumping right in. Not sure where to start? Investigate licensed forex trading blockchain platforms, open a demo account, and observe this technology in action.

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Studying no longer has physical weight — it lives on screens, in tabs, and in constant notifications. That shift has made student life faster and more flexible, but also harder to switch off.

There was a time when studying had a certain physical weight to it. Heavy textbooks, printed lecture notes, library cards, folders full of half-understood material. A student could almost measure the semester by the mess on the desk. Now, much of that weight has disappeared into screens. It sounds convenient, and often it is, but something more complicated has happened too. Student life has not simply become easier. It has become faster, more exposed, more flexible, and, in some ways, harder to escape.

Technology in student life is not only about laptops and online classes. It is about the way students think, plan, panic, communicate, compare themselves, and recover from failure. A missed lecture can be watched later. A difficult concept can be searched in seconds. A group project can be completed without anyone sitting in the same room. At the same time, attention is constantly under attack. The same device that opens a Stanford lecture also opens TikTok, messages, games, and a dozen unfinished tabs. That pull is measurable: a 2025 HEPI–Kortext survey of UK undergraduates found 92% now use AI tools in their studies, up from 66% the year before — a sign of how fast digital habits are moving through campus life.

For many students, especially at college and university level, digital tools now shape the entire academic routine. A student may start the day checking Google Calendar, download readings from Moodle or Canvas, join a Zoom seminar, use Grammarly to polish an essay, ask ChatGPT for brainstorming help, and finish with a YouTube explanation of a topic the professor made sound impossible.

The academic writing support online for students is for those who need structured academic writing help during intense study periods, especially when deadlines, part-time work, and coursework begin to collide. That does not mean technology replaces learning. The real question is how technology affects students when digital support becomes part of almost every decision around learning.

The student’s day has become less linear

Before digital learning became normal, studying usually followed a clearer pattern: attend class, take notes, read, write, submit. Now a student’s day is fragmented. A person may study in short bursts between work shifts, public transport, family responsibilities, and social media interruptions. This is one of the biggest changes in educational technology for students: learning has become portable.

That portability is powerful. A student working part-time can listen to a recorded lecture at night. Someone who feels shy in class can ask questions in a discussion forum. International students can translate unfamiliar words instantly. Students with disabilities can use screen readers, captions, speech-to-text tools, and digital planners.

A digital essay writing service can also become part of this wider support system when students need help understanding structure, academic tone, citation logic, or the expectations behind a difficult assignment. Used responsibly, that kind of support works best as guidance rather than a substitute for thinking.

Still, flexibility has a hidden cost. When studying can happen anywhere, it can also feel as if it should happen everywhere. Rest becomes suspicious. Free time starts to feel inefficient. A student may close the laptop and still feel followed by unread notifications from university platforms.

Digital tools changed how students solve problems

The biggest shift is not access to information. It is access to immediate help. Twenty years ago, confusion lasted longer. A student who did not understand a concept had to wait for office hours, ask a classmate, or search through books. Now confusion often lasts thirty seconds.

Common digital tools for students include:

This changes confidence. Students are less dependent on one teacher or one textbook. A weak lecture does not automatically mean weak understanding. If a professor explains statistics badly, a student can find another explanation from Khan Academy, MIT OpenCourseWare, or a random educator on YouTube who somehow makes regression analysis sound normal.

But there is a strange side effect. When help is always available, patience becomes thinner. Some students become uncomfortable sitting with difficulty. They expect every problem to have a quick explanation, a template, or a shortcut. Real learning often requires slowness, and technology is not naturally slow.

Online learning made education more democratic, but not equal

The impact of technology on education is often described in bright language: access, innovation, personalization. Some of that is true. During the COVID-19 pandemic, universities across the world moved online almost overnight. Harvard, Oxford, the University of California system, and thousands of smaller institutions had to rethink teaching quickly. At its peak, UNESCO recorded more than 1.6 billion learners in over 190 countries out of school — the largest disruption to education in history. It was messy, but it proved something important: education could continue outside the classroom.

For students in remote areas, online education can be life-changing. For working students, it can be the difference between staying enrolled and dropping out. For students who learn better at their own pace, recorded lectures are not a luxury. They are a survival tool.

Yet technology did not remove inequality. It exposed it. UNESCO found that half the world’s students lacked a household computer during the pandemic, and 43% had no internet access at home. Not every student has a quiet room, fast internet, a good laptop, or parents who understand why silence matters during an exam. A student attending class from a crowded kitchen is not experiencing the same digital education as someone with a private study room and a MacBook.

So, how technology affects students depends heavily on their environment. The tool may be the same. The experience is not.

Communication became easier, and sometimes colder

Technology has made communication faster. Students can message professors, collaborate through Google Docs, join Discord study groups, and receive feedback without waiting for the next class. Group projects no longer require everyone to meet in a library at 5 p.m.

But faster communication is not always better communication. Students may receive too many messages from too many platforms — email, Slack, WhatsApp, university portals, group chats. Important information gets buried. A deadline may be announced in one place, changed in another, and discussed in a third.

There is also the emotional distance. A student can disappear from an online course more quietly than from a physical classroom. No one sees the tired face, the confusion, the embarrassment. Digital education can be efficient while still feeling lonely.

Technology changed academic pressure

One uncomfortable truth: students are now surrounded by comparison. LinkedIn shows classmates getting internships. Instagram shows beautiful study desks and color-coded notes. Productivity apps turn studying into performance. Even learning can become aesthetic.

This pressure is subtle. A student may not only ask, “Am I studying enough?” but also, “Am I studying in the right way? Using the right apps? Building the right profile?” Technology creates opportunities, but it also creates the feeling that everyone else is moving faster.

At the same time, academic dishonesty has become more complicated. AI tools can generate essays, solve equations, summarize books, and imitate academic tone. That shift is already showing up in how students themselves feel about it: RAND’s American Youth Panel found AI use for homework rose from 48% to 62% between May and December 2025, even as 67% of students said the habit was eroding their critical thinking. Universities now face a difficult task: they must teach students how to use these tools responsibly instead of pretending they do not exist. Banning everything is lazy. Allowing everything is careless. The answer is somewhere in the uncomfortable middle.

The future student will need judgment, not just access

The student of the future will not be the one who knows the most facts. Facts are already everywhere. The stronger student will be the one who can judge quality, ask better questions, notice weak arguments, manage attention, and use technology without becoming passive.

Educational technology for students should not only make tasks faster. It should make thinking deeper. A calculator did not destroy mathematics. Google did not destroy research. AI will not automatically destroy writing. But each tool changes what effort means.

A good student now needs a different kind of discipline. Not just “study harder,” but choose carefully. Which tool helps? Which one distracts? Which shortcut teaches something, and which one quietly removes the learning?

What students may need to understand next?

Technology has changed student life in obvious ways: online classes, digital textbooks, AI tools, instant research, flexible schedules. But the bigger change is emotional. Students live with more possibility and more noise. They can learn almost anything, but they must fight harder to focus on one thing.

Maybe that is the real story. Technology did not make student life simple. It made it wider — more open, more demanding, more personal. A student today carries a university, a library, a tutor, a planner, and a distraction machine in one pocket. What happens next depends less on the device itself and more on whether students are taught how to use it with intention.

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Dubai is known for its fast-paced lifestyle, where balancing work, family, and personal commitments can leave little time for household chores. It’s a city built around convenience — roughly 92% of Dubai’s resident population are expatriates, many drawn by demanding careers, and about 81% of the population is economically active, meaning most households are juggling full-time jobs alongside everything else on their plate. Among these daily demands, laundry is often one of the most time-consuming tasks. This is why professional laundry services have become an increasingly popular solution for residents across the city.

Why Professional Laundry Makes Sense

Doing laundry at home involves more than simply washing clothes. Sorting garments, treating stains, drying, ironing, and folding can take several hours each week — data from the American Time Use Survey shows that an average person spends more than 62 hours a year on laundry alone, the equivalent of nearly three full working days. By choosing a professional laundry service, you can save valuable time while ensuring your garments receive expert care.

Modern laundry providers also use commercial-grade equipment and specialized cleaning techniques that help preserve fabric quality, extend garment life, and deliver a deeper clean than most household machines. This isn’t just marketing — ENERGY STAR-certified commercial washers use about 45% less water and run roughly 9% more efficiently than standard residential models, which translates into gentler, more consistent care for fabrics over repeated washes.

Convenience That Fits Your Lifestyle

One of the biggest advantages of using a laundry service is the convenience of pickup and delivery. Instead of planning your day around laundry, you can schedule a collection that fits your routine and have your freshly cleaned clothes returned directly to your home or office.

For busy professionals, families, students, and frequent travelers, this convenience makes a noticeable difference in day-to-day life. It also explains why the market has kept expanding. According to Mordor Intelligence, the UAE’s laundry appliances and services sector is projected to grow from around $371.29 million (2025) to $489.19 million by 2030, a compound annual growth rate of 5.67%, driven largely by rising demand from both commercial and residential customers in cities like Dubai.

More Than Just Washing Clothes

Today’s professional laundry companies offer a wide range of services beyond standard wash and fold, including:

• Dry cleaning for delicate garments
• Professional ironing and pressing
• Curtain and upholstery cleaning
• Carpet and rug cleaning
• Commercial laundry solutions for businesses

These services ensure every fabric receives the appropriate treatment while maintaining its appearance and longevity. For hospitality-heavy cities like Dubai, where hotels, restaurants, and offices all depend on consistent linen and uniform care, having a single provider capable of handling both household and commercial volumes adds a layer of reliability that in-house laundry simply can’t match at scale.

Choosing the Right Laundry Service

When selecting a laundry provider in Dubai, consider factors such as reliability, customer reviews, turnaround time, pricing transparency, and garment care standards. A trusted provider should offer consistent quality, convenient scheduling, and responsive customer support.

With expat households often managing multiple jobs, school runs, and travel schedules, the value of a laundry partner that shows up on time and delivers consistent results compounds quickly — a single missed pickup or a poorly handled garment can cost far more in hassle than the service itself.

Across the Emirate’s neighborhoods, the best laundry service in Dubai looks less like a luxury add-on and more like a dependable pickup-and-delivery partner — one that fits around your schedule and treats every garment with the same care you would at home, minus the hours spent doing it yourself.

Final Thoughts

Professional laundry services are no longer considered a luxury — they’ve become a practical solution for people who value their time and want their clothes professionally maintained. With Dubai’s population and job market continuing to grow, and household laundry remaining one of the most time-consuming chores families face, outsourcing it has moved from convenience to near-necessity for many residents. Whether you need weekly laundry, expert dry cleaning, or ironing services, outsourcing your laundry can simplify your routine while ensuring consistently high-quality results.

Choosing a trusted provider like Laundry Khalas allows you to spend less time on household chores and more time enjoying everything Dubai has to offer.

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Saicon Consultants, a US-based technology services company, has acquired Pragmatyc Group Private Limited, a Nagpur-based firm specialising in enterprise AI, AIoT, intelligent automation, and digital engineering. The deal marks Saicon’s third India-linked acquisition in a short span, following its purchase of SilverSearch in the United States and Valethi Technologies, also based in Nagpur.

Founded in 1998, Saicon provides technology, engineering, and consulting services to more than 80 enterprise customers through delivery operations spanning the US and India, with a workforce of over 1,600 employees. Pragmatyc brings expertise in computer vision, predictive analytics, and data engineering, capabilities the company says will strengthen Saicon’s ability to connect physical operations, enterprise data, and AI-driven intelligence for its clients.

“The acquisition of Pragmatyc strengthens Saicon’s capabilities in two areas that are becoming increasingly important to our clients — Enterprise AI and AIoT. By combining Pragmatyc’s expertise with Saicon’s global client relationships and delivery scale, we will be better positioned to help enterprises build intelligent, connected and more efficient operations,” said Ramesh Lokre, founder and CEO of Saicon Consultants

Pragmatyc’s founder framed the deal as a natural next step for a company that has spent recent years building deep, narrow expertise in AI engineering.

“Joining the Saicon Group is an exciting milestone in Pragmatyc’s journey. This partnership gives us the opportunity to combine our AI engineering expertise with Saicon’s global reach, enabling us to deliver innovative Enterprise AI solutions to customers worldwide while creating exciting growth opportunities for our team,” said Praful Lichade, founder and CEO of Pragmatyc

The acquisition reflects a broader pattern among US technology services firms, which are increasingly buying rather than building AI and AIoT expertise inside India’s tier-2 tech hubs, where specialised engineering talent is available at a lower cost base than in metro tech centres. Nagpur’s emergence as a repeat target for Saicon, following Valethi Technologies, suggests the company sees the city specifically, not just India broadly, as a delivery hub worth consolidating around.

For enterprises evaluating AI vendors, the deal signals a continued shift toward combining edge-to-cloud intelligence, where sensor data, industrial systems and AI models are stitched together across a single stack, rather than sourced from separate specialist vendors. Saicon has framed its recent acquisition run as a deliberate strategy to deepen expertise in high-growth technology areas while expanding its US market presence and global delivery footprint, positioning the combined Saicon-Pragmatyc business to compete for enterprise AI contracts that increasingly require both engineering depth and operational scale.

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Noida-based Leverage Edu has bought Brazil-based Mundus Agency, its first acquisition outside India and its debut in the South American market. The deal gives the study-abroad platform a direct foothold in one of the world’s fastest-growing outbound education corridors, where nearly 90,000 Brazilian students head overseas for higher education each year, a figure that has climbed roughly 50% since 2017.

Financial terms of the transaction were not disclosed. Mundus Agency works with universities and institutions across multiple countries, specialising in student recruitment, admissions counselling, and university partnerships, capabilities that slot directly into Leverage Edu’s existing stack of study-abroad admissions support, financing, and accommodation services.

The timing is not incidental. Leverage Edu, founded in 2017 by Akshay Chaturvedi, Aman Arora, and Digvijay Gagneja, is preparing for a public listing in India and has already opened conversations with investment bankers. The company is reportedly eyeing an IPO in the ₹2,000-3,000 Cr range, split between a fresh issue and an offer-for-sale, at a valuation north of $900 million. Bankers have positioned the startup alongside platform businesses like Zomato and ixigo when pitching comparable valuation multiples, a sign of how far the company has moved from being viewed purely as an admissions counselling shop.

That shift shows up in the numbers. Leverage Edu’s operating revenue more than doubled to ₹375 Cr in FY26 from ₹173 Cr a year earlier, and the company says it turned EBITDA profitable during the year. Its horizontal push, spanning fintech, accommodation, travel, and career support alongside its original admissions business, now makes up 25-33% of total revenue. The startup added more than 55,000 students to its platform in the past fiscal year, taking its cumulative user base past 1.75 lakh.

Buying into Brazil fits a broader pattern among Indian study-abroad platforms, which have spent the past two years diversifying beyond the traditional UK-US-Canada-Australia funnel as visa tightening in those markets pushed students toward alternative destinations. Brazil’s outbound diaspora, now close to 50 lakh people, including students, skilled professionals, and healthcare workers, represents exactly the kind of underserved, high-growth pool that a platform preparing for public-market scrutiny needs to show it can capture.

Before this deal, Leverage Edu’s footprint spanned South Asia, Africa, and the Middle East. Extending into Latin America builds a more global growth story heading into the IPO process, at a time when investors are increasingly parsing edtech pitches for real geographic diversification rather than single-market dependence. The company has raised $57.3 million in funding to date from investors, including Blume Ventures and BlackSoil.

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AI and ML are changing the industry around the world. From making product recommendations on e-commerce sites to advanced healthcare solutions and smart business solutions, AI and ML are becoming an important part of modern technology. With more and more companies implementing AI and ML in their businesses, the need for skilled personnel is increasing day by day. The scale of this shift is already visible in the numbers — the global economy has added 1.3 million new AI-related jobs in just two years, according to LinkedIn data cited by the World Economic Forum.

It opens up some really exciting possibilities for freshers, but one question remains — What kind of skills do you need to land yourself in that all-important first job in AI and Machine Learning?

Most students believe that it takes a lot of experience or expertise to get into the domain of AI and machine learning. It is not always the case; many times, employers require those who have solid fundamentals and are able to think on their feet. Getting enrolled in an AIML course is an ideal way to acquire these skills.

Let us find out what skills freshers should possess in order to start a career in AI and Machine Learning.

Strong Programming Skills

Programming forms the basis of AI & ML.

Candidates must have a good grasp of writing neat and optimized code. They should be able to apply their knowledge of programming fundamentals to solve real-world problems.

For example, consider an organization that is planning to develop an intelligent customer service solution. Before developing the AI model, they must first write the program to collect, process data, and implement the logic. Python’s dominance in this space keeps growing — its usage jumped 7 percentage points between 2024 and 2025 alone, according to Stack Overflow’s Developer Survey, largely on the strength of its role in AI and data science work.

Key areas to focus on include:

• Writing efficient code
• Understanding data structures
• Problem-solving through programming
• Debugging and testing applications
• Building small practical projects

A strong programming foundation makes it easier to learn advanced AI concepts later.

Understanding Machine Learning Fundamentals

Many freshers focus on tools without understanding the underlying concepts. Employers, however, often value fundamental knowledge.

A candidate should understand:

• What Machine Learning is
• How models learn from data
• Different learning approaches
• Model training concepts
• Evaluation and improvement techniques

For example, consider an online streaming platform recommending movies to users. Understanding how recommendation systems learn user preferences helps freshers connect theory with real-world applications.

A quality AI ML Course typically introduces these concepts through practical examples and projects.

Data Analysis Skills

It does not matter how good AI algorithms are; they still require high-quality data to produce meaningful outputs. It is important for beginners to know how to analyze and interpret information properly.

Suppose that you get customer purchase data from an organization. You have to structure your data and check whether it is accurate before creating any Machine Learning model. This is not a minor step — surveyed data scientists report spending as much as 80% of their time on preparing and cleaning data rather than modelling it, a pattern documented in a well-known Forbes-reported survey.

Important skills include:

• Data cleaning
• Data preparation
• Data visualization
• Pattern identification
• Data interpretation

Employers appreciate candidates who can work with data confidently and extract meaningful insights.

Mathematical and Analytical Thinking

Although it is not necessary for freshers to be mathematicians, knowledge of basic concepts enables them to learn how models work.

What is more important, analysis enables experts to think logically about problems.

For instance, if an artificial intelligence model comes up with unforeseen results, then analytical skills enable one to determine the problem and how best to rectify it.

Problem-solving skills are usually the hallmark of successful candidates in interviews and project meetings.

Knowledge of AI Tools and Frameworks

The domain of artificial intelligence comprises numerous technologies that facilitate the creation of intelligent systems effectively.

As a fresher, one must familiarize oneself with some popular development environments used in Machine Learning. This isn’t a passing trend — AI and big data top the list of fastest-growing skills employers expect to need through 2030, ahead of networks, cybersecurity, and general technological literacy, according to the World Economic Forum’s Future of Jobs Report.

For instance, when a firm is trying to build an image recognition app, the candidates are expected to know the usage of AI technology in building and implementing the models.

Gaining knowledge about such technologies by taking up the AIML course would benefit freshers.

Project Building Skills

One of the biggest challenges for freshers is gaining experience before getting their first job.

Personal projects help bridge this gap.

Employers often value candidates who can demonstrate practical work rather than relying only on academic qualifications. In fact, 76% of hiring managers say self-taught skills and portfolio work can outweigh formal education when evaluating a candidate, according to Resume Genius survey data.

Examples of beginner projects include:

• Sentiment analysis applications
• Recommendation systems
• Predictive analytics solutions
• Chatbots
• Image classification projects

Imagine two candidates applying for the same role. Both have similar educational backgrounds, but one has developed several AI projects and can explain their learning journey. That candidate is often more likely to leave a strong impression.

Projects showcase technical skills, initiative, and genuine interest in the field.

Problem-Solving Ability

AI professionals spend a lot of time solving business problems.

There is rarely any requirement in the industry to employ someone just to make a model. The company needs professionals who can analyze a problem and implement technology to solve it. This is reflected in what employers say they value most — around 88% of employers screen for problem-solving ability in candidates, making it the single most sought-after skill in hiring, according to the NACE Job Outlook 2025 survey.

For instance, a logistics firm requires a solution to identify the issues that may lead to late deliveries. It is more about finding a solution to a business problem rather than making an AI model.

Those freshers who show their structured thinking skills and problem-solving abilities become popular.

Communication Skills

Communication is something that many students don’t realize is important in technical fields.

AI professionals work on projects in which they often communicate with people from the management and client sides who are non-technical.

Knowing how to convey ideas effectively becomes an important trait. Employers back this up in practice: nine out of ten talent professionals and hiring managers say soft skills like communication are as important, or more important, than technical skills, with communication topping LinkedIn’s own list of most in-demand skills.

For instance, once a machine learning model is built, the person needs to be able to tell the advantages of it to business people. The technical part alone won’t do.

Good communication skills can help freshers get a job and succeed in their career.

Curiosity and Continuous Learning

The AI industry evolves rapidly.

New tools, techniques, and applications emerge regularly. Employers look for candidates who demonstrate curiosity and a commitment to learning. That pace of change is measurable — employers expect 39% of the core skills required in today’s job market to change by 2030, according to the World Economic Forum’s Future of Jobs Report.

A fresher who actively explores new technologies, experiments with projects, and stays updated on industry developments often stands out.

Learning does not stop after completing an AI ML Course. In fact, continuous learning becomes an essential part of a successful AI career.

Teamwork and Collaboration

AI projects typically involve multiple stakeholders, including developers, data analysts, business managers, and domain experts.

Freshers who work well with others are often more successful in professional environments. LinkedIn’s own workforce data shows this pays off in tangible career terms — professionals with teamwork listed as a skill are promoted 11% faster than those without it.

Collaboration skills help individuals:

• Share ideas effectively
• Learn from experienced team members
• Contribute to group projects
• Adapt to workplace dynamics
• Build professional relationships

Employers value candidates who can contribute positively to team success.

To Sum Up

Getting your first job in the fields of Artificial Intelligence and Machine Learning might be tough, but it is not at all difficult if freshers learn how to hone their skills properly. Good knowledge about programming, basics of Machine Learning, data analysis skills, problem-solving skills, and communication skills are essential for an excellent AI career.

Moreover, practical projects, analytics, teamwork, and the capability to learn continuously can make candidates more appealing to prospective employers. An effective AIML Course or AI ML Course can be of great assistance to freshers by preparing them through proper guidance and exposure.

But the most successful AI professionals may not necessarily be the ones who know everything right from the beginning. They are rather the ones who keep learning and keep using their learning to solve relevant problems. For all freshers who want to make it big in this amazing field, such traits should serve as a good starting point for their careers ahead.

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Workforce systems become important when a start-up begins hiring faster than its founders can manage every decision. Informal agreements may work with ten people, but they become harder to apply fairly once teams expand, managers take on staff, and new starters need the same information.

The aim is to put enough structure in place for people to know how work gets done, what support they receive, and where decisions are recorded. These systems don’t need to be complicated, but they should work for a larger team than the one you have now.

Keep Employee Information in One Place

Store contracts, role details, leave records, and policy acknowledgements in one secure system. Decide who can view or update each type of information, because shared folders and private messages quickly become hard to follow. Joining up onboarding, induction, and training processes means every new starter receives the same information, even when different managers are involved. 80% of businesses use HR software — meaning roughly 1 in 5 still don’t, which is the scattered-spreadsheets/shared-folder problem this section is about.

Build a Consistent Benefits Package

Decide which benefits the company will offer, who qualifies, and how staff will hear about changes. One-off arrangements may feel generous, but they’re difficult to explain later when two people in similar roles receive different support. Working with employee benefits consultants gives founders a clearer way to compare workforce needs, costs, and recruitment plans before choosing a package. Good employee benefits consulting also covers enrolment, renewals, and the questions employees are likely to ask. A Gallup survey found that 64% of workers rate income or benefits as “very important” when weighing a job offer, which is why inconsistent packages carry more risk than founders often expect.

Make Hiring and Onboarding Repeatable

Write down what happens from an approved vacancy to the end of probation, including who signs off on salary, interviews candidates, checks references, sends documents, and prepares equipment. Managers still need room to judge each appointment, but they shouldn’t have to invent the process every time.

Give one person the responsibility for checking that new starters have the right accounts, equipment, and training. A missing login or unclear policy is easier to sort out early than after someone has spent months finding a workaround or relying on a colleague to fill the gap. Structured onboarding programmes lead to 58% higher three-year retention than informal ones, according to research summarised by Management.org, which is exactly the gap a repeatable process closes.

Make It Clear Who Decides What

Once several people share responsibility for hiring, spending, or customer work, confusion often appears in small delays. Two managers may think the other person is approving a request, or an employee may not know who can settle an issue. Keep role descriptions current and spell out who owns decisions in each team. Clear performance formulas also help employees understand what they’re being judged on without turning every review into a debate. Update responsibilities whenever the work changes instead of saving everything for an annual review. Nearly half of employees say they lack clarity about their own role, and that gap is exactly where the small delays described above start to appear.

Create a Monthly People Check-In

Once a month, bring managers together to talk through workload, upcoming hires, absence, team concerns, and roles that are becoming difficult to cover. Keep a short record of what was agreed and who is following it up, but don’t turn the meeting into a long reporting exercise. Employees whose managers hold regular meetings with them are almost three times as likely to be engaged as those who don’t, according to Gallup research.

This gives founders a view of where extra support or recruitment may be needed. It also creates a place to discuss development, pay questions, and succession plans as the company grows. Start with a simple agenda and keep the parts that help managers make better decisions.

The post Five Workforce Systems to Build Before Your Start-up Doubles in Size appeared first on LAFFAZ.

Every bootstrapped founder eventually hits the same fork: build the company website and product on WordPress, or pay for a custom stack. The pitch for WordPress has always been the same — cheaper, faster, familiar to whoever the founder hires next. The pitch against it has always been the same, too — plugin bloat, security patching, and a ceiling on what it can actually do without a developer who really knows the codebase.

That calculation is shifting, and the reason is AI tooling that can now work inside a live WordPress installation instead of just generating code in a chat window.

What Actually Changed

Until recently, asking an AI assistant for help with a WordPress project meant describing your setup in a prompt, copying back an error, and repeating the cycle until something worked. The AI never actually saw your site — your plugins, your database, your custom post types. It was a guess.

That’s changed with the Model Context Protocol (MCP), an open standard originally built by Anthropic that lets AI tools connect directly to a system and act on it — not just talk about it. Applied to WordPress, an MCP-connected AI can read theme files, inspect database tables, and check which plugins are active before it suggests anything, rather than working from a generic description of the problem.

A handful of tools are already built around this. Services like WPVibe AI connect an MCP server straight to a WordPress site so the AI works from the real install rather than a text summary of it, with theme changes staged as drafts and previewed before anything touches the live site. Code editors, including Cursor and Zed, now support MCP connections too, letting a developer query a WordPress environment directly from the editor instead of pasting context back and forth.

Why This Matters For The Buy-vs-Build Decision

WordPress still runs a large share of the internet — 41.5% of all websites, more than any other content management system by a wide margin. The reason it kept that lead even as no-code builders multiplied is the same reason it’s relevant to this shift: an enormous ecosystem of plugins, themes, and developers that a custom stack has to rebuild from scratch. The knock against it was always the labor cost of maintaining that ecosystem safely. AI tooling attacks that specific cost.

Tasks that used to require a specialist — writing a custom REST API endpoint, setting up ACF field groups programmatically, auditing a site full of undocumented plugins from a previous developer — are more approachable when the AI can see exactly what the installation looks like before it writes anything. For a founder paying by the hour or the project, that compresses the two things that make WordPress expensive in practice: the time spent debugging conflicts, and the time spent explaining the project to whoever inherits it.

It doesn’t erase the case for a custom stack. A product with heavy real-time functionality, unusual data models, or performance demands still outgrows WordPress fast, AI or not. But for a marketing site, a content-driven site, or a straightforward SaaS front end, the cost gap that used to push founders toward “just build it custom” is narrower than it was a year ago.

The Part Founders Still Need To Own

None of this removes the need for judgment. An AI that can read a database schema can still write a query that runs but performs badly under load. An AI that knows every plugin on a site can still recommend an integration that quietly breaks something else. The tooling raises the ceiling on what one developer can competently handle — it doesn’t lower the bar on what “competent” means.

For a founder evaluating a dev shop or freelancer, the practical takeaway is to ask directly whether they’re using this kind of tooling, and to still expect them to explain trade-offs rather than defer entirely to what the AI suggests. The permissioning question — what the AI can read, what it can change, and what needs a human sign-off first — is still being worked out across the ecosystem, and it’s worth asking about explicitly before handing over site access.

A Quick Framework

• Lean WordPress + AI tooling if the site is content-first, needs a non-technical team member to manage it day to day, and doesn’t depend on custom real-time features.
• Lean custom stack if the product itself is the software — complex logic, heavy data processing, or performance-critical user flows that WordPress was never built to carry.
• Either way, ask about MCP-style tooling upfront. It changes the cost and timeline conversation with any dev partner, and it’s a fair question to ask before signing anything.

The gap between “cheap and limited” and “capable but expensive” was the whole argument for skipping WordPress. That gap is what’s actually closing — not WordPress’s relevance, which was never really in question.

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When Info Edge‘s board approved a ₹39.91 crore buyout of the remaining 45.36% stake in Coding Ninjas on July 6, most coverage treated it as a routine cap-table cleanup — a company that had backed an edtech platform since 2020 finally taking full ownership. That framing undersells what the deal actually is: the fourth time in six years Info Edge has converted a startup bet into a wholly owned subsidiary, and a useful marker for how differently Indian edtech companies are being absorbed, rescued, or wound down as the sector’s post-pandemic reckoning runs its course.

Info Edge’s ownership playbook has a consistent shape, even when the entry points differ. With Zwayam, an AI-powered recruitment software company, Info Edge went straight for 100% ownership in 2021, paying roughly ₹61 crore ($8.3 million) to bring it in as a full subsidiary within weeks of announcing the deal. DoSelect (operated by Axilly Labs) was folded in the same year through a similar direct buyout. Highorbit Careers, the parent of recruitment platforms iimjobs and hirist, was acquired outright in FY2019-20. In each of these cases, Info Edge skipped the minority-stake phase entirely — it bought the whole business in one motion because the target filled a specific gap next to Naukri.com’s core recruitment business.

Coding Ninjas followed a different arc, and that difference is the more interesting part of the story. Info Edge first backed the coding-education platform’s Series A round in 2020, then increased its holding to a majority stake through follow-on transactions in 2022, before this month’s deal closed out the remaining minority position. The payment itself is structured in deferred tranches — 25% at closing, the rest spread across three annual instalments through 2029 — a structure that lets Info Edge complete full ownership without a large upfront cash outlay. That’s a meaningfully different signal than the Zwayam-style instant buyout: it reads less like an urgent acquisition and more like a company converting a long-held minority position into full control once it had enough confidence in the unit economics to justify the balance-sheet commitment.

And the underlying numbers support that reading. Coding Ninjas isn’t a distressed asset being absorbed to prevent a collapse. Its revenue grew from roughly ₹53 crore in FY24 to about ₹67 crore in FY25 and nearly ₹97 crore in FY26, with losses narrowing over the same period. This is a company on an improving trajectory, not one that needed rescuing, which makes the full-ownership move look more like portfolio tidiness than crisis management. Info Edge gets direct control over integrating Coding Ninjas’ course catalogue with Naukri’s broader upskilling push, without managing that integration through a shared cap table.

That distinction matters because it sits in sharp contrast to what’s happening elsewhere in Indian edtech right now. The sector’s most consequential deal this year was upGrad‘s acquisition of Unacademy through an all-stock, share-swap transaction announced in March 2026 — a deal widely read as signalling that India’s edtech story has entered a consolidation phase rather than continuing its pandemic-era expansion. Unlike Coding Ninjas, Unacademy wasn’t a healthy business quietly converting a stake — its valuation had fallen more than 85% from a 2021 peak of $3.5 billion to under $500 million, and the deal arrived after the company disclosed roughly $100 million in cash reserves following a year of consolidating company-run centres with franchise partners. Unacademy co-founder Gaurav Munjal acknowledged as much publicly, writing that the company had “lost some focus and market share” and that the sector itself “has not seen enough real product innovation in recent years.”

At the harsher end of the same spectrum sits BYJU’S, whose collapse from a $22 billion valuation into insolvency proceedings remains the sector’s starkest cautionary tale — a case study in what happens when aggressive acquisition-fuelled growth outruns the underlying unit economics. Investors, including Prosus and BlackRock, eventually wrote their stakes down to zero.

Set against those two, PhysicsWallah represents a third and very different path: it stayed disciplined through the funding winter, turned profitable, and completed a public listing in November 2025 at a premium to its issue price — proof that at least one large edtech player found a way to scale without needing either a rescue acquisition or a distressed sale.

Read together, these four situations — Info Edge/Coding Ninjas, upGrad/Unacademy, BYJU’S, and PhysicsWallah — sketch out the range of exits now available to Indian edtech companies as the sector matures past its 2021 boom. A founder with a fundamentally sound but sub-scale business, sitting inside a larger diversified parent that already holds a majority stake, can convert into a wholly owned subsidiary on favourable, deferred terms — a comparatively quiet, founder-friendly landing. A founder whose valuation has collapsed but who retains a meaningful market position can find a strategic buyer willing to absorb the business via a share swap, trading independence for survival. A founder who badly overextends on acquisition-led growth without matching fundamentals risks the BYJU’S outcome. And a small number of disciplined operators will simply out-execute the correction entirely and go public on their own terms.

What the Coding Ninjas deal specifically demonstrates is that full-ownership consolidation doesn’t have to mean distress. Info Edge has now run this playbook four times, and the through-line across Zwayam, DoSelect, Highorbit Careers, and Coding Ninjas is control over adjacent capabilities that reinforce Naukri’s and its portfolio’s core businesses, executed at a pace and structure that suits Info Edge’s own balance sheet rather than any external pressure on the target. That’s a meaningfully different kind of consolidation than the one reshaping the rest of India’s edtech sector — and one worth watching as more Info Edge-backed minority stakes mature toward similar decisions in the coming years.

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The Competition Commission of India has approved upGrad’s proposed acquisition of Unacademy, clearing a major regulatory hurdle for a deal that has been years in the making. The CCI cleared the transaction under Section 31(1) of the Competition Act, 2002, covering upGrad’s acquisition of a stake in Sorting Hat Technologies Private Limited, Unacademy’s parent entity, and its subsequent merger into upGrad Education. A detailed order is expected to follow.

The all-stock deal values Unacademy at approximately ₹2,055 Cr, or roughly $218 million, a nearly 90% discount to the $3.4 billion valuation the edtech company commanded in 2021 at the peak of pandemic-era online learning demand. upGrad first signed a term sheet for the acquisition in March this year, after an earlier round of merger talks between the two companies had collapsed over valuation disagreements.

The regulatory clearance lands against a backdrop of upGrad’s own improving financial position. The company, led by co-founder and chairman Ronnie Screwvala, raised ₹361 Cr in May at a valuation of roughly $1.73 billion, with participation from existing backers Temasek, the International Finance Corporation and 360 ONE Opportunities Fund. upGrad has also turned the corner operationally, posting a provisional profit after tax of ₹38 Cr on revenue of ₹1,532 Cr over the first eleven months of FY26, against a loss of ₹273.7 Cr the previous fiscal year. The company expects Unacademy to add close to ₹500 Cr to its consolidated revenue once integration is complete.

Unacademy’s path to this point tells a familiar story for India’s post-pandemic edtech sector. Founded in 2015 by Gaurav Munjal, Roman Saini, and Hemesh Singh, the company raised roughly $830 million from investors including Peak XV Partners, Blume Ventures, and Elevation Capital during its rapid ascent. As offline coaching resumed and investor appetite cooled, Unacademy exited parts of its offline operations, bought back ₹50 Cr worth of employee stock options, and pivoted toward a leaner, more capital-efficient model. Leadership also shifted this year, with Sumit Jain stepping down as full-time CEO and co-founder Munjal resuming direct operational oversight.

The deal extends upGrad’s acquisition-led growth strategy, which has included the purchase of internships and careers platform Internshala and more than half a dozen other companies since 2022. For India’s edtech sector broadly, the transaction is the latest signal that scale alone no longer guarantees survival, and that consolidation, rather than fresh funding, is increasingly how founders and investors are finding an exit path out of businesses built during the 2020-21 funding boom.

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Digital health platform ekincare has acquired Superclaims, an AI-powered claims adjudication SaaS platform that automates one of healthcare’s most document-heavy and error-prone processes by integrating directly with an insurer’s or TPA’s existing workflow.

As part of the acquisition, Superclaims cofounder and CEO Bhavish Ramaswamy and cofounder and CTO Maneesh Daithala, along with the leadership team, will continue in their roles and report to ekincare’s senior leadership. The Superclaims brand will continue operating independently while drawing on ekincare’s broader platform and distribution network.

The deal is expected to expand ekincare’s presence across insurers and TPAs, increase wallet share within its existing enterprise base, and create cross-sell opportunities between the two businesses. It also positions the combined entity to expand beyond India as an AI-powered SaaS platform for insurance companies globally.

Co-founded in 2014 by Kiran Kalakuntla and Srikanth Samudrala, Hyderabad-based ekincare is a personalised, full-stack health benefits platform that helps employers design benefits packages suited to employees and their families. The company serves 2 million employees across more than 1,000 organisations, including Fortune 500 clients such as PepsiCo, BlackRock, and Visa, backed by a network of over 90,000 healthcare providers across more than 500 cities.

ekincare raised $15 million in a Series B round led by HealthQuad and Sabre Partners in March 2022, with participation from Ventureast, Eight Roads Ventures, Siana Capital, and Endiya Partners.

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Nikhil Kamath-led WTF has acquired Mumbai-based creative agency BTG (By The Gram), marking its second acquisition in the creative services space after One Hand Clap (OHC).

Founded in 2018 by Aaliya Amrin, Eman Batliwalla, and Danisha Kohli, BTG will continue to operate independently under its existing leadership, with its founders and team retaining operational and creative control. As part of the deal, BTG gains access to capital, WTF’s network, and its distribution infrastructure, positioning the agency to pursue larger client mandates.

BTG works with brands including Netflix, Prime Video, IKEA, Volkswagen, Bumble, Soho House, Marriott, and Nykaa, providing strategy and creative services across beauty, hospitality, entertainment, technology, tourism, and consumer sectors. Going forward, the agency plans to focus on deeper client relationships, investment in owned content and intellectual property, and expansion of its senior leadership team.

The acquisition comes amid rising investor interest in founder-led creative agencies. Through its purchases of OHC and now BTG, WTF is building a portfolio of creative businesses spanning branding, content and strategy — extending Kamath’s investment footprint beyond his core fintech and wealth management ventures into the consumer and marketing services space.

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Zostel has approached the Securities and Exchange Board of India, urging the regulator to examine disclosures made by Oravel Stays, OYO’s parent operating under the brand PRISM, in its updated draft red herring prospectus filed ahead of its planned IPO. In a 56-page representation submitted on July 3, followed by a reminder on July 7, Zostel alleged that the offer document presents an incomplete account of its long-running legal dispute with OYO and asked SEBI to examine whether the disclosures meet completeness, fairness, and materiality standards under the SEBI Act and ICDR Regulations.

The dispute stems from a non-binding 2015 term sheet under which OYO proposed to acquire Zostel’s hotel business, with Zostel’s shareholders set to receive up to a 7% equity stake in OYO in return. The deal collapsed, leading to arbitration in 2018. A 2021 arbitral tribunal, headed by a former Chief Justice of India, ruled that OYO had breached the agreement, but the Delhi High Court later set aside that award in May 2025, holding that the term sheet was non-binding and did not create enforceable rights. The Supreme Court declined to entertain Zostel’s appeal against that ruling in July 2025.

Zostel maintains that appellate proceedings are still pending before the Delhi High Court and should be reflected in OYO’s IPO disclosures. A Zostel spokesperson confirmed the SEBI filing, clarifying that the company is seeking a review of the IPO disclosures rather than a determination of the underlying legal dispute. OYO has disputed Zostel’s claims.

On a parallel track, the Delhi High Court disposed of Zostel’s fresh application in the same dispute on July 10, with the underlying appeal now listed for hearing on August 12. PRISM’s draft prospectus itself discloses the litigation and warns that an adverse ruling could require the company to issue or transfer up to 7% of its share capital, or pay an equivalent amount, with potential implications for its business, financial condition, and shareholding structure.

OYO’s proposed IPO comprises a fresh issue of equity shares worth up to ₹6,650 crore, with no offer-for-sale component, meaning existing investors, including SoftBank’s SVF Holdings, Microsoft, Airbnb, and Peak XV Partners, will not dilute their stakes.

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Elevate Education, the Gurugram-based higher education platform formerly known as Sunstone, has secured ₹170 crore in a Series D round from WestBridge Capital, an existing backer, as it looks to strengthen its technology stack and deepen AI use across the student lifecycle.

Founded in 2019 by Ashish Munjal, Ankur Jain, and Piyush Nangru, Elevate Education partners with colleges and universities to deliver undergraduate and postgraduate programmes combining industry-oriented curricula, placement support, and technology-enabled student services.

The company currently supports more than 25,000 active students across 22 campuses in 15 cities, and expects to reach ₹300 crore in revenue and profitability in FY27.

“India’s higher education system is at an inflection point,” said Munjal, Co-founder and CEO of Elevate Education. “The future of higher education will not be defined by who awards the degree, but by who delivers the best learner outcomes. This investment from WestBridge Capital strengthens our ability to scale responsibly, invest in innovation, and build one of India’s most trusted higher education platforms.”

Sandeep Singhal, Co-founder and Managing Partner at WestBridge Capital, said the firm believes Elevate Education is “addressing an important opportunity in India’s education ecosystem by improving the quality and relevance of learning at scale.” WestBridge has previously backed companies including Rapido, Meesho, PhysicsWallah, LEAD Group, Star Health, and IndiGo.

The fresh capital arrives as India’s higher education sector undergoes structural change driven by the National Education Policy 2020, which has encouraged multidisciplinary learning, flexibility in degree structures, and wider digital adoption.

Elevate had previously raised close to $70 million from investors including Prime Venture Partners, Alteria Capital, and Saama Capital, with its most recent Series C — a $35 million round led by WestBridge — closing in August 2022.

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WizCommerce, an AI-native sales and ecommerce platform for wholesale distributors, has raised ₹79.5 crore (around $8.3 million) in a fresh funding round from existing investors Blume Ventures, Alpha Wave, Z47, 100X.VC and Peak XV Partners. The round extends the company’s runway less than a year after its $8 million Series A, led by Peak XV Partners in August 2025.

According to regulatory filings with the Registrar of Companies, WizCommerce’s board allotted 7,565 bridge compulsorily convertible preference shares at ₹1,05,051 apiece to raise the capital. Blume Ventures led the round with ₹28.72 crore, followed by Alpha Wave at ₹23.94 crore, Peak XV Partners at ₹14.36 crore, Z47 at ₹7.65 crore and 100X.VC at ₹4.79 crore. Following the allotment, Blume Ventures holds the largest external stake at 17.49%, ahead of Peak XV Partners at 15.57%, Alpha Wave at 14.85%, Z47 at 10.38% and 100X.VC at 2.61%.

Founded in 2020 by Divyaanshu Makkar, a former Bessemer Venture Partners executive, and Vikas Garg, a former Zomato executive, WizCommerce operates on a SaaS subscription and transaction-driven model, helping wholesale distributors digitise quoting, storefronts, ERP integrations and payments. The platform processes more than $100 million in annual GMV across over 700 sales reps and 300,000 buyers, serving categories including home décor, lighting and general merchandise.

Speaking of the development, Sajith Pai, Partner at Blume Ventures, said the team has “built a product stack that U.S. wholesalers and distributors absolutely love, reflected in their rapid revenue growth,” pointing to the company’s ship-fast culture and new product launches such as WizAI and WizStudio.

The fresh round will support continued product development and go-to-market expansion into adjacent verticals, the company said.

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