AlleyWatch sat down with Kubera Health Founder and CEO Roja Garimella, MD to learn more about the business, its future plans, recent $6.5M seed round that brings total funding to $9.5M, and much, much more…

Who were your investors and how much did you raise?

We raised a $6.5M seed round, led by Upfront Ventures, with Company Ventures, Dria Ventures, and SemperVirens Venture Capital participating.

Tell us about the product or service that Kubera Health offers.

Kubera Health is the contract-to-payment system of record for American healthcare — contract and payment intelligence for providers and the organizations that serve them. We turn every payor-provider contract into structured rules that run against claims and financial data, so that payment issues can be audited and reconciled against the contract itself.

What inspired the start of Kubera Health?

I trained as a medical doctor and started my career on the clinical side, but I’d had a long-standing frustration with why the administrative side of healthcare is so hard. Working inside large enterprises like Humana and Commonwealth Care Alliance, I saw firsthand how difficult the operations around contracts and data really were — the hardest problems weren’t clinical, they were financial. Kubera exists to fix one of the biggest issues within healthcare: how care gets paid for and how expensive that process is.

How is Kubera Health different?

Most companies in this space work downstream — in the claim queue, the denial workflow, the billing staff. We work upstream, at the contract layer where the rules originate. Providers lose revenue because they don’t fully know what their contracts say, can’t model what they should be paid, and have no systematic way to tell when a payment deviates from contracted terms. By making those contract terms computable, measurable, and enforceable, we help prevent that leakage structurally rather than chasing it after the fact. We’re building infrastructure, not another workflow tool.

What market does Kubera Health target and how big is it?

U.S. healthcare spending is around $5 trillion a year, and roughly a quarter of that — close to $1 trillion — goes to administration rather than care. We’re focused on the financial layer inside that: the contracts, claims, and payments that move money between payors and providers, which alone runs about $200 billion a year across more than nine billion claims. It’s a massive market, and it’s still remarkably dominated by very old and disconnected technology.

What’s your business model?

We charge a subscription fee based on volume, scale, and complexity, and we’ve increasingly been moving into upside arrangements and shared-risk models alongside that.

How are you preparing for a potential economic slowdown?

We’re full steam ahead on growth right now. Healthcare generally fares well in challenging markets, and administrative spend has only continued to increase. As conditions get tougher and government funding to healthcare programs comes under pressure, hospitals and clinics feel every dollar more acutely — so we’re preparing to help more of them recoup the payments they’re owed and negotiate stronger contracts to weather harder economic times.

What was the funding process like?

We’d worked closely with most of these investors for over a year prior, so there was already a foundation of trust and a shared understanding of what we were building that made the process efficient.

What are the biggest challenges that you faced while raising capital?

Raising capital is always a distraction from the core business, and everything else keeps moving full steam ahead regardless, so the hardest part was keeping all the balls in the air at once. There’s also a real education curve: this is a complex, unglamorous corner of healthcare, and part of the work is helping investors understand why the contract layer is the right place to build.

What factors about your business led your investors to write the check?

We had strong pilot conversion and net revenue retention across our first batch of customers, and we’d proven we could get deep into sales processes with some of the largest healthcare enterprises in the country.

We had strong pilot conversion and net revenue retention across our first batch of customers, and we’d proven we could get deep into sales processes with some of the largest healthcare enterprises in the country.

What are the milestones you plan to achieve in the next six months?

We have several flagship feature releases coming over the next few months — including work in agentic revenue recovery that I’m especially excited about.

What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?

Build for your customers, and keep your team in the loop every step of the way. It sounds simple, but those two habits are what keep you honest and aligned when you don’t have a fresh injection of capital to paper over mistakes.

Where do you see the company going now over the near term?

We’re building toward becoming the system of record that healthcare payments actually run on. Near term, that means supporting more customers and variations of contracts/payment models.

What’s your favorite spring destination in and around the city?

Red Hook — best views in the city, great food, and so many fun places to explore.

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New York City venture capital delivered $2.01 billion across 75 companies in May 2026, a 12.0% increase from April fueled by one of the city’s strongest multi-deal months on record. Seven NYC startups each raised $100 million or more — a concentration of large rounds rarely seen outside months anchored by a single outlier raise. Modal Labs led with $355 million for its AI cloud infrastructure platform, but the month’s character was defined less by any one deal than by the breadth of capital flowing into mature, revenue-stage companies across healthcare, insurance, fintech, and AI infrastructure. Four of the top 10 deals — Vi Labs, Reserv, Garner Health, and Nourish — collectively raised $471 million, underscoring a quiet but substantial reorientation of NYC late-stage capital toward health and insurance technology. AI-identified companies captured 66% of all funding deployed, with $1.32 billion spread across 32 startups spanning clinical AI, insurance automation, investment management, and cybersecurity.

NYC Venture Capital Activity by Stage — May 2026

Top 10 NYC Venture Capital Deals — May 2026

Modal Labs Leads a Strong Month for AI Infrastructure

Modal Labs’ $355M late-stage round was the defining deal of May, cementing the company’s position as one of NYC’s most heavily backed AI infrastructure plays. The serverless cloud platform, which enables developers to run machine learning and data processing workloads without managing infrastructure, has become a critical layer in the AI development stack. At 17.7% of all NYC capital deployed in May, Modal’s raise single-handedly elevated the month’s headline figure and anchored a broader pattern: AI infrastructure and tooling companies attracted a disproportionate share of late-stage investment in May.

OpenRouter’s $113M Series B added another dimension to the AI infrastructure story. The platform, which routes AI applications to large language models and cloud hosting providers, raised at a moment when enterprises are actively building out multi-model strategies. Together, Modal and OpenRouter alone accounted for $468M — nearly 23% of all NYC capital in May.

Series B Activity Surges on Retail and AI Bets

May’s Series B cohort stood out as the most active by average deal size, with nine rounds totaling $454.9M at a $50.5M mean — well above what the stage typically produces in NYC. RADAR’s $170M raise was the key driver. The retail technology company, which uses computer vision and RFID to automate in-store inventory tracking and checkout, raised one of the larger Series B rounds seen in the NYC market this year. RADAR and OpenRouter together represented 61.2% of all Series B capital in May, which skewed the stage average significantly; the median of $33.0M is a more representative figure for the rest of the cohort.

AI Captures Two-Thirds of NYC Capital

Thirty-two of 75 funded NYC companies in May were identified as AI-focused, accounting for $1.32B — 66% of all capital deployed locally. The concentration is notable not just for its magnitude but for its spread across verticals: Vi Labs ($146M) applies AI to healthcare and life sciences, Reserv ($125M) uses it for insurance claims processing, Moment ($78M) for investment management, and Frame Security ($50M) for cybersecurity. The month illustrated how AI has moved from a descriptor for foundational model companies to an operational layer embedded across insurance, health, finance, and enterprise software.

Of the top 10 NYC deals in May, seven involved companies with AI at the core of their product — a ratio that reflects both investor appetite and the continued maturation of AI-native business models in the city’s startup ecosystem.

NYC vs. US National Venture Capital Activity — May 2026

NYC accounted for 3.0% of US venture capital by dollars in May 2026, a figure significantly compressed by Anthropic’s $50B Series H — the largest venture round in recorded history — which single-handedly concentrated the national headline. Stripping out Anthropic, NYC’s share of the remaining $17.03B in US activity would be approximately 11.8%, a more historically representative reading of the city’s standing. NYC’s 18.3% share of national deal count reflects a market that punches above its weight at the volume level. The city’s strongest competitive position was at Series B, where it captured 18.1% of national capital across 22.5% of deals.

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Looking Ahead

With $2.01B deployed in May, NYC has now posted back-to-back months above $1.7B — a level of consistency that signals healthy underlying demand rather than episodic spikes. The Series B cohort’s strength is worth watching: nine rounds at a $50.5M average suggest a group of companies that raised Series A capital in 2023 and 2024 are now reaching the scale inflection where larger follow-on checks are warranted. If that pipeline holds, June could see continued Series B activity as more of that cohort completes their fundraising cycles. The health and insurance verticals, each producing two top-10 deals in May, have emerged as recurring themes in NYC’s late-stage market and bear watching as AI-native applications in both spaces continue to attract investor interest.

Methodology

Data for this report is sourced from AlleyWatch proprietary funding data (funding.alleywatch.com) and covers venture capital rounds announced or closed in May 2026 by NYC-headquartered startups. Deals are classified into four stages: Early-Stage (pre-seed, seed, angel, accelerator, and incubator rounds); Series A; Series B; and Late-Stage (Series C and beyond). AI company classification is based on the presence of relevant keywords across company description and industry fields. All figures are in USD.

11. H1.co $40M

Round: Venture
Description: H1.co provides healthcare data and analytics that help organizations identify and engage medical experts. Founded by Ariel Katz, Ian Sax in 2017, H1.co has now raised a total of $233.9M in total equity funding and is backed by Menlo Ventures, Y Combinator, IVP, Lux Capital, and Flex Capital.
Investors in the round: CVS Health Ventures
Industry: Biotechnology, Health Care, Life Science, Medical, Therapeutics
Founders: Ariel Katz, Ian Sax
Founding year: 2017
Total equity funding raised: $233.9M

10. Cinder Technologies $41M

Round: Series B
Description: Cinder Technologies provides trust and safety, content moderation, and data labeling tools for AI applications. Founded by Glen Wise, Philip Brennan in 2021, Cinder Technologies has now raised a total of $55M in total equity funding and is backed by Accel, Radical Ventures, Y Combinator, Pioneer Fund, and J2 Ventures.
Investors in the round: Accel, M12 – Microsoft’s Venture Fund, Outpost Ventures, PSP Growth, Radical Ventures, Y Combinator
Industry: Artificial Intelligence (AI), Data Collection and Labeling, Developer APIs, Fraud Detection, Information Technology, Intelligent Systems, Risk Management
Founders: Glen Wise, Philip Brennan
Founding year: 2021
Total equity funding raised: $55M

9. Pace $46M

Round: Series B
Description: Pace provides an AI-powered operations platform for insurance companies. Founded by Jamie Cuffe in 2024, Pace has now raised a total of $56M in total equity funding and is backed by Sequoia Capital, Thrive Capital, Emergence Capital, and PruVen Capital.
Investors in the round: Emergence Capital, PruVen Capital, Sequoia Capital, Thrive Capital
Industry: Artificial Intelligence (AI), Insurance, InsurTech, Software
Founders: Jamie Cuffe
Founding year: 2024
Total equity funding raised: $56M

8. Daloopa $47M

Round: Series C
Description: Daloopa provides financial data and modeling tools for investment research and AI-driven workflows. Founded by Daniel Chen, Jeremy Huang, Thomas Li in 2019, Daloopa has now raised a total of $101.4M in total equity funding and is backed by Nexus Venture Partners, Morgan Stanley, Liquid 2 Ventures, Touring Capital, and Hack VC.
Investors in the round: Brighton Park Capital, Nexus Venture Partners, Squarepoint Capital, Touring Capital
Industry: Analytics, Artificial Intelligence (AI), Big Data, Financial Services, Software
Founders: Daniel Chen, Jeremy Huang, Thomas Li
Founding year: 2019
Total equity funding raised: $101.4M

AlleyWatch’s exclusive coverage of this round: Daloopa Raises $47M to Make AI-Driven Investment Research Reliable and Auditable

7. Frame Security $50M

Round: Venture
Description: Frame Security provides AI-powered cybersecurity software focused on human risk management and security awareness. Founded by Tal Shlomo, Sharon Shmueli in 2025, Frame Security has now raised a total of $50M in total equity funding and is backed by Index Ventures, Team8, Picture Capital, Tesonet, and Assaf Rappaport.
Investors in the round: Assaf Rappaport, Cerca Partners, Gil Capital, Index Ventures, Picture Capital, Team8, Tesonet
Industry: Information Technology, Internet
Founders: Tal Shlomo, Sharon Shmueli
Founding year: 2025
Total equity funding raised: $50M

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6. Moment $78M

Round: Series C
Description: Moment provides AI-powered software for investment and wealth management operations. Founded by Ammer Soliman, Dean Hathout, Dylan Parker in 2022, Moment has now raised a total of $134M in total equity funding and is backed by Andreessen Horowitz, Lightspeed Venture Partners, Index Ventures, Neo, and Venrock.
Investors in the round: Andreessen Horowitz, Avra Capital, Index Ventures
Industry: Analytics, Finance, Financial Services, FinTech, Risk Management, Software
Founders: Ammer Soliman, Dean Hathout, Dylan Parker
Founding year: 2022
Total equity funding raised: $134M

5. Nourish $100M

Round: Series C
Description: Nourish provides insurance-covered nutrition counseling through a network of registered dietitians. Founded by Aidan Dewar, Sam Perkins, Stephanie Liu in 2021, Nourish has now raised a total of $213.1M in total equity funding and is backed by Menlo Ventures, BoxGroup, TCV, Thrive Capital, and Index Ventures.
Investors in the round: Atomico, BoxGroup, Daybreak ventures, Index Ventures, J.P. Morgan Growth Equity Partners, Maverick Ventures, Menlo Ventures, Operator Partners, Thrive Capital, Y Combinator
Industry: Apps, Health Care, Nutrition, Telehealth
Founders: Aidan Dewar, Sam Perkins, Stephanie Liu
Founding year: 2021
Total equity funding raised: $213.1M

5. Garner Health $100M

Round: Series E
Description: Garner Health helps employers connect employees with high-performing healthcare providers. Founded by Nick Reber in 2019, Garner Health has now raised a total of $319.3M in total equity funding and is backed by BoxGroup, Sequoia Capital, Thrive Capital, Abstract, and Founders Fund.
Investors in the round: Founders Fund, Index Ventures, Kaiser Permanente Ventures, Kleiner Perkins, Redpoint, Sequoia Capital, Thrive Capital
Industry: Big Data, Business Intelligence, Employee Benefits, Health Care, Software
Founders: Nick Reber
Founding year: 2019
Total equity funding raised: $319.3M

4. OpenRouter $113M

Round: Series B
Description: OpenRouter provides a platform that connects AI applications to large language models through a unified API. Founded by Alex Atallah, Chris Clark, Louis Vichy in 2023, OpenRouter has now raised a total of $153M in total equity funding and is backed by Andreessen Horowitz, Menlo Ventures, Sequoia Capital, Transpose Platform Management, and NVentures.
Investors in the round: Andreessen Horowitz, CapitalG, Databricks Ventures, Menlo Ventures, MongoDB Ventures, NVentures, ServiceNow Ventures, Snowflake Ventures
Industry: Artificial Intelligence (AI), Information Technology, Software
Founders: Alex Atallah, Chris Clark, Louis Vichy
Founding year: 2023
Total equity funding raised: $153M

3. Reserv $125M

Round: Series C
Description: Reserv provides an AI-powered insurance claims platform for managing property and casualty claims. Founded by CJ Przybyl, Martha Dreiling, Oleg Ilichev in 2022, Reserv has now raised a total of $209.1M in total equity funding and is backed by Flourish Ventures, 8VC, Bain Capital Ventures, Anthemis, and Accenture Ventures.
Investors in the round: Bain Capital Ventures, Flourish Ventures, Kohlberg Kravis Roberts & Co.
Industry: Consulting, Financial Services, Insurance, Property Insurance
Founders: CJ Przybyl, Martha Dreiling, Oleg Ilichev
Founding year: 2022
Total equity funding raised: $209.1M

2. RADAR $170M

Round: Series B
Description: RADAR provides retail technology that automates in-store inventory tracking, analytics, and checkout operations. Founded by Adam Blair, Michael E. Murphy, Spencer Hewett in 2013, RADAR has now raised a total of $217M in total equity funding and is backed by Y Combinator, Nimble Partners, Colle Capital Partners, NTT DOCOMO Ventures, and Gideon Strategic Partners.
Investors in the round: Align Ventures, Gideon Strategic Partners, Nimble Partners
Industry: Computer Vision, E-Commerce, Retail, Retail Technology, RFID
Founders: Adam Blair, Michael E. Murphy, Spencer Hewett
Founding year: 2013
Total equity funding raised: $217M

1. Modal Labs $355M

Round: Series C
Description: Modal Labs provides serverless cloud infrastructure for running machine learning and data processing workloads. Founded by Akshat Bubna, Erik Bernhardsson in 2021, Modal Labs has now raised a total of $465.5M in total equity funding and is backed by General Catalyst, Accel, Menlo Ventures, Gaingels, and Creandum.
Investors in the round: Accel, Bain Capital Ventures, General Catalyst, Menlo Ventures, Redpoint
Industry: AI Infrastructure, Cloud Computing, Cloud Data Services, Information Technology, Software, Web Development
Founders: Akshat Bubna, Erik Bernhardsson
Founding year: 2021
Total equity funding raised: $465.5M

AlleyWatch sat down with Daloopa CEO and Co-founder Thomas Li to learn more about the business, its future plans, recent funding round that brings the company’s total funding raised to $101.4M, and much, much more…

Who were your investors and how much did you raise?

We raised a $47M Series C led by Brighton Park Capital, with participation from Squarepoint Capital, Touring Capital, and Nexus Venture Partners.
The financing comes at a point where investment firms are starting to move AI into real production workflows across research, valuation, and analysis, which is increasing the importance of having reliable, auditable financial data infrastructure underneath those systems.

Tell us about the product or service that Daloopa offers.

Daloopa provides structured, source-linked financial data infrastructure that powers financial institutions’ research workflows.
Historically, a lot of financial analysis has depended on analysts manually pulling and entering data from sources including company filings, investor presentations, and press releases, then validating the accuracy of each datapoint. That process is time-consuming and becomes even more challenging once AI systems start relying on that data – or web-scraped inputs – at scale.
Daloopa’s platform covers more than 5,500 public companies globally, with each datapoint linked back to its original source for auditability. Investment firms use the platform across workflows like valuation, modeling, research, and reporting, and increasingly as part of AI and agentic workflows as well.

What inspired the start of Daloopa?

The original inspiration for Daloopa really came from seeing how much of financial analysis still depended on highly manual work. Even at some of the most sophisticated investment firms in the world, analysts were spending huge amounts of time pulling numbers from filings, cleaning data, checking sources, and rebuilding the same workflows over and over again in Excel.
At the time, that was already inefficient for humans, but we also realized it was going to become a much bigger problem once AI systems started getting applied to financial workflows. If the underlying data is inconsistent or not traceable back to original source documents, the outputs become unreliable very quickly.
So the idea behind Daloopa was to build a structured, source-linked financial data layer that investment firms could actually trust and use in production workflows.

How is Daloopa different?

I think one of the biggest differences is that we built Daloopa around where financial workflows are going, especially as AI becomes part of how investment research and analysis get done.
Historically, the process was highly manual, with analysts spending a huge amount of time collecting, entering, and validating financial data before they could even begin the actual analysis work. What’s changing now is that AI can automate a lot of that work, but only if the underlying data is reliable and structured correctly.
The other major difference is the depth of the dataset itself. We go very deep at the company level, and customers are increasingly using Daloopa not just inside traditional models and research workflows, but directly inside platforms like ChatGPT, Claude, Perplexity, and Rogo.

What market does Daloopa target and how big is it?

We primarily serve financial institutions, including hedge funds, mutual funds, bulge-bracket banks, and increasingly AI-native financial platforms.
The broader market is financial data and financial infrastructure, given the introduction of AI and agentic workflows at financial institutions. As firms start operationalizing AI across research, modeling, valuation, and reporting, the demand for reliable underlying financial data increases significantly.

What’s your business model?

Daloopa provides a SaaS subscription that includes access to its comprehensive financial dataset, an Excel-native modeling assistant, and its data layer via MCP to drive AI workflow adoption. The company also offers programmatic access via API and cloud-native delivery through Snowflake, Databricks, and AWS S3.
Historically, most customers used Daloopa through more traditional research and modeling workflows, but over the last couple of years we’ve also seen growing adoption through AI platforms and agentic workflows. That includes customers using our data directly inside tools like ChatGPT, Claude, Perplexity, and Rogo.

How are you preparing for a potential economic slowdown?

Our focus is on solving a real problem that’s becoming even more critical as AI adoption in financial services increases.
If anything, firms are under more pressure to improve efficiency and productivity, and that tends to accelerate interest in automation and AI-driven workflows rather than slow it down.

What was the funding process like?

It was a very thoughtful process. We spent a lot of time talking with investors who really understood the nuances of data businesses and financial infrastructure specifically, because this is a very different type of company than a typical application software business.
What ultimately stood out with Brighton Park was their depth of understanding around the importance of data quality, accuracy, and long-term infrastructure value in financial services.

What are the biggest challenges that you faced while raising capital?

I think one of the biggest challenges is that data businesses are very nuanced businesses. In our world, small differences in data quality and accuracy matter a lot to customers, especially once AI is used inside real investment workflows.
So a big part of the process was finding investors who really understood the importance of the underlying data layer and appreciated the complexity behind building it well.

What are the milestones you plan to achieve in the next six months?

A big focus for us over the next several months is continuing to expand the depth and coverage of the dataset itself. We already cover more than 5,500 public companies globally, but we want to go deeper across the companies.
We’re also investing heavily in AI and agent workflows on top of the data layer, particularly around products like Scout and other tools that help customers automate parts of research, modeling, and analysis workflows.
And then more broadly, we’re continuing to expand integrations and partnerships across the AI ecosystem as adoption accelerates across financial services.

What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?

I think the biggest thing is staying very focused on the customer and solving their biggest challenges. The best way to find product-market fit is to solve a real problem your customers care deeply about.

What’s your favorite spring destination in and around the city?

Going for a run in Central Park.

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Now look at what actually drives the money. DraftKings announced at its 2026 investor day that online casino already generates roughly 25% of revenue but close to 50% of EBITDA, despite being legal in only eight US states versus 32 for sports betting. The business that VCs funded most enthusiastically turns out to be a customer acquisition channel for the business VCs barely touched. That structural mispricing is starting to get noticed.

For founders and investors in the gaming space, and for the startups building infrastructure around real money online play, the next window may be considerably more interesting than the one that just closed. And the consumer-facing layer where all of this lands, the best online casinos for real money, is growing faster than the capital markets have yet priced in.

The Sports Betting Playbook and Its Limits

The case for backing sports betting startups was never really about sports betting. It was about customer acquisition at scale in a newly legal market, and the hope that once users were inside the app, higher-margin products would follow. That thesis has proven correct faster than most expected.

But the funding dynamics stayed locked in place long after the strategic reality shifted. Traditional VC firms continued to back sportsbooks and daily fantasy platforms. Real money online casino, regulated under the same frameworks in the same states, was treated as a different category entirely: too close to gambling in the uncomfortable sense, too dependent on regulatory timing, too capital-intensive before a single dollar of revenue appeared.

The result is a market that generated $400M in US gross gaming revenue in 2025 across eight states, is projected to approach $3B by 2030, and has received a fraction of the venture attention that far smaller sports betting markets attracted at equivalent stages.

Why Standard VCs Have Stayed Away

The structural reasons are real and worth understanding before dismissing them. Licensing is long and expensive. A single-state online casino license can take six to twelve months and costs millions.

Payment rails are complicated: banks treat gambling transactions as high-risk, which creates friction at every stage from customer deposits to operator payroll. And the LP base at most mainstream VC funds includes institutional investors with explicit restrictions on gambling exposure.

The due diligence process also looks different. Metrics like CAC, LTV, and monthly active users mean something different in a regulated gambling context. Player reinvestment rates, hold percentages, and GGR margins are the operating vocabulary, and most generalist investors do not speak it.

The result is that founders in this space have had to find specialist capital, often from operators, private equity, or industry-specific funds, rather than from the Valley infrastructure that backs most other consumer tech categories.

As Will Ventures argued in a March 2026 investment thesis, this represents a genuine mispricing. The secular trends behind online casino growth, rising gambling participation, mobile penetration, digital payment normalization, and state-by-state legalization, are all moving in one direction.

The talent moving into the sector from finance and tech is accelerating. And the infrastructure plays that sit underneath the consumer layer, compliance tooling, payment orchestration, responsible gaming software, and identity verification, are exactly the kind of B2B SaaS opportunities that VC firms understand and fund without the regulatory discomfort attached to operating a casino directly.

The Infrastructure Layer Is Where the Startup Opportunity Lives

This distinction matters for founders. Building a licensed real money casino in New Jersey is a different challenge from building the compliance infrastructure every licensed casino in New Jersey needs to buy. The latter is a classic SaaS motion: recurring revenue, low churn, strong expansion within accounts, and a moat built on regulatory expertise that competitors cannot replicate overnight.

Responsible gaming software is one example. Every licensed operator is required to offer self-exclusion tools, session timers, and affordability checks under increasingly strict regulatory frameworks. Very few operators build this in-house. The same applies to identity verification, AML monitoring, payment orchestration, and affiliate attribution. Each of these is a startup opportunity that benefits from gaming industry tailwinds without requiring a gambling license of its own.

For players navigating the consumer end of this market, the infrastructure investments by operators translate directly into a better, more trustworthy experience. Independent directories that aggregate licensed platforms, player reviews, and bonus terms help new entrants find the best online casinos for real money without exposure to unlicensed operators, which remain a significant share of the market in states where regulation has not yet caught up with consumer demand.

The Next Five Years

New York is the single biggest variable. If the largest US media market legalizes online casinos, the revenue figures will be rewritten and the venture appetite will follow. Illinois, Virginia, and Massachusetts are each in various stages of legislative consideration. The momentum is slow but directional.

Meanwhile the international picture is moving faster. Brazil launched in January 2025 and is expected to become one of the world’s largest markets. New Zealand is licensing operators for a December 2026 launch. France is legalizing online casino alongside its existing regulated betting sector. Each new regulated market creates licensing fees, compliance requirements, and platform opportunities that specialist founders and investors can move on before generalists even notice.

The bet that mainstream VC missed on real money gaming is not over. It is setting up again, in infrastructure, in new markets, and in the operator layer that still has room to run.