Israel is participating disproportionately in this shift. Israeli defence-tech startups working with the Ministry of Defence reportedly raised nearly $3 billion in the first half of 2026, three times the amount raised during all of 2025. Defence-tech and dual-use companies accounted for almost 30% of the $8.4 billion invested in Israeli high-tech during the period, while approximately 800 startups are now fulfilling direct procurement orders for the Ministry of Defence.

These numbers came to mind during my visit to Los Angeles this week, where I met several investors who have backed Israeli startups or are actively looking to do so. While LA is still best known for Hollywood, gaming and consumer technology, another ecosystem has been building—quite literally—in the industrial corridors stretching from El Segundo and Hawthorne to Long Beach and Orange County.

Southern California is becoming one of the world’s most important hubs for defence, aerospace and advanced manufacturing. SpaceX is headquartered in Hawthorne. Anduril was founded in Orange County and is significantly expanding its Southern California presence. Around them is a growing constellation of companies developing autonomous systems, satellites, drones, sensors, advanced materials and new manufacturing technologies.

You can feel that defence tech is no longer a niche category in LA. It is becoming part of the region’s identity and, increasingly, part of the conversation among its investors. I believe Israel is undergoing a similar shift.

Defence tech is commercialised deep tech

What makes defence tech particularly interesting is that it is often commercialised deep tech: difficult, defensible technology applied to an identifiable problem, with a customer that has both an urgent need and a budget.

Deep-tech startups have traditionally faced a difficult commercialisation challenge. They may possess impressive intellectual property and potentially transformative technology, but it can take years to identify a customer willing to fund its deployment. Defence can change that equation because the problems are visible, the consequences of failure are tangible and the need for better solutions is immediate.

Modern defence technology combines many of the disciplines in which Israel has longstanding expertise: artificial intelligence, computer vision, autonomy, robotics, cybersecurity, electronic warfare, semiconductors, edge computing, sensors, communications, space technology and advanced manufacturing.

These are not isolated military technologies. Many have meaningful applications in logistics, industrial automation, transportation, emergency response, agriculture, energy and the protection of critical infrastructure. The most interesting defence-tech companies are not necessarily traditional weapons manufacturers. They are technology companies solving hard problems in autonomy, resilience, sensing, coordination and production. Defence may be their first or most demanding customer, but it does not always have to be their only market.

Five frontiers shaping the market

Bessemer Venture Partners recently published its 2026 defence technology roadmap, arguing that defence technology has advanced more in the past 24 months than during the preceding three decades. Bessemer identifies five areas likely to define the next generation of national-security innovation: autonomy, AI-powered defence workflows, advanced manufacturing, resilient networks, and energy and materials independence.

The first frontier is autonomy moving from experimentation into deployment. The opportunity is no longer limited to building an individual drone or autonomous vehicle. It is expanding into coordinating large numbers of heterogeneous systems across air, land, sea and space, including the command-and-control infrastructure required to manage them.

The second is AI entering both mission-critical and administrative defence workflows. Defence organisations deal with enormous quantities of unstructured information, complex planning processes and fragmented legacy systems. As AI becomes more reliable and deployable in secure, air-gapped or disconnected environments, it can improve intelligence analysis, mission planning, procurement, maintenance and logistics.

The third is advanced manufacturing. Recent conflicts have exposed an uncomfortable reality: Western countries are not equipped to manufacture many critical systems cheaply, quickly or at sufficient volume. The next generation of defence companies will need to innovate in production as much as in product design. A better interceptor is of limited value if it costs several million dollars to stop a drone costing a few thousand, or if it cannot be manufactured quickly enough to replace depleted inventory.

The fourth is resilient communication and navigation. GPS, conventional communications and centralised networks are vulnerable to jamming, spoofing and attack. The modern battlefield increasingly requires mesh networks, self-healing communications and alternative positioning technologies capable of operating in contested environments.

The fifth is energy and materials independence. Defence capability ultimately depends on access to energy, critical minerals, batteries, semiconductors and secure supply chains. Technological sovereignty is not just about owning the software or intellectual property; it is also about retaining the ability to manufacture the underlying systems.

These categories closely match areas in which Israeli founders already possess relevant technical and operational experience.

Why Israel could repeat its cyber success

Israel’s defence industry is not new. Rafael, Elbit Systems and Israel Aerospace Industries have spent decades building globally recognised capabilities. What is changing is the emergence of a much larger startup layer around these established companies.

The shift is visible in an unlikely place: Israel’s office market. According to a recent CTech report, office leasing by Israeli defence and security companies increased by 32% in the first half of 2026, reaching more than 140,000 square metres. Companies in the sector were seeking a further 145,000 square metres, representing roughly 30% of all active demand in Israel’s office market.

Real estate can be a useful lagging indicator of what is happening underneath the funding announcements. Defence companies need laboratories, clean rooms, testing facilities, secure infrastructure and physical production space. They also tend to have less flexibility to embrace remote work. Their expansion into Tel Aviv and other technology centres suggests that they are increasingly competing directly with software companies for engineering talent.

There are structural reasons why Israel should be strong in this category. The country has dense networks connecting military units, universities, defence contractors, entrepreneurs and investors. Founders frequently encounter operational problems before they become visible to the wider commercial market. They are accustomed to building under constraints, combining hardware and software and deploying products in situations where failure has real consequences.

Most importantly, Israeli founders can benefit from unusually fast feedback loops. Technology can be developed, tested and improved through close interaction with sophisticated users. This resembles Israel’s original advantage in cybersecurity: the best founders do not begin with an abstract market thesis. They begin with intimate knowledge of the problem.

Cybersecurity did not become an Israeli specialty because Israel simply had good engineers. It became a repeatable company-building engine because founders emerged with relevant experience, found early customers, attracted specialist investors, successfully entered the US market and then trained or financed the next generation of founders. Defence tech may now be developing the same flywheel.

The LA–Israel defence-tech bridge

This is where Los Angeles becomes particularly relevant. Israel may be exceptionally good at producing technologies and technical founders, but Israeli defence startups still require access to the US market. They need American customers, manufacturing partners, regulatory expertise, specialist capital and people who understand how to navigate the US procurement system.

Southern California offers much of that infrastructure in one place. Its advantage extends beyond SpaceX and Anduril. The region has a deep aerospace heritage, experienced engineering talent, industrial capacity, major research universities and a growing community of founders trained inside the new generation of defence and space companies. In fiscal 2023 alone, Los Angeles County received approximately $12 billion in defence contracts.

The ecosystem is also producing important second-order effects. Employees leave successful companies to launch new startups. Investors develop a better understanding of government procurement and hardware risk. Suppliers become accustomed to working with fast-growing companies rather than only established defence primes. Talent, capital, customers and manufacturing knowledge begin to reinforce one another.

For Israeli founders, LA can therefore become more than a source of investment. It can be a landing point for entering the American defence ecosystem, developing local partnerships and eventually establishing manufacturing or commercial operations in the US.

For LA investors, Israel offers something equally valuable: a concentrated source of founders with operational experience, distinctive technical capabilities and products developed in response to real-world needs. The fit is natural, but stronger bridges will be required to turn that potential into repeatable outcomes.

This is not simply cyber with hardware

There are important differences between defence tech and Israel’s cyber boom. A cybersecurity startup can often sell its first product to a commercial enterprise, improve it remotely and expand through a relatively conventional software sales model. Defence companies face longer procurement cycles, security restrictions, export controls and considerable customer concentration.

Hardware creates additional risk. Manufacturing delays cannot be fixed with another software release. Scaling production requires working capital, supply-chain expertise, quality assurance, facilities and specialised personnel. A successful demonstration proves that a technology can work; it does not prove that the company can deliver hundreds or thousands of units reliably, safely and at an acceptable cost.

Capital is also becoming concentrated in a relatively small number of large rounds. Record investment totals do not necessarily mean it has become easy for a new defence startup to raise its first institutional round. As we have seen elsewhere in venture capital, headline funding can obscure a much more selective early-stage environment.

Investors must also confront the regulatory and ethical consequences of the sector. “Dual use” should not become a convenient label attached to every technology with a potential military customer. Founders and investors need clear policies regarding end users, permitted applications, exports and governance. These questions cannot be postponed until after the company achieves product-market fit.

Israel’s next global category

Cybersecurity emerged from a combination of talent, experience, networks, customer access and repeated success. The same ingredients are increasingly present in defence technology, amplified by geopolitical urgency, the progress of AI and autonomy, growing defence budgets and a procurement system becoming somewhat more open to startups.

Israel is already one of the world’s leading centres for defence innovation. The question is whether its next generation of founders can turn that capability into independent, globally significant technology companies.

My conversations in Los Angeles this week reinforced my belief that this is bigger than a local Israeli investment trend. LA and Israel occupy complementary positions in the same emerging ecosystem. One offers access to the world’s largest defence market, specialist capital and a rapidly growing industrial base; the other offers an unusually concentrated supply of technology, talent and operational insight.

If the right bridges are built, defence tech could become for Israel what cybersecurity became over the past two decades: not simply a successful sector, but a durable global advantage.

The original version was published on LinkedIn to 8,200+ subscribers.

Firgun (pronounced ‘feer-goon’) is an Israeli term describing genuine, unselfish joy in someone else’s success… It’s basically the opposite of “schadenfreude”. Every week since March 2020, we celebrate the wins of our startup community. Read more about why Firgun matters. If this was forwarded to you and you’d like to subscribe, previous editions are on VC Cafe.

Greetings from Los Angeles, my inspiration for this week’s image. I met with all sorts of investors who are interested in Israeli startups. The news from President Trump of the demilitarisation of H***s could be fantastic news, if enforced. Against that backdrop, Israeli tech delivered another remarkable week, with the cyber and AI-agent-security boom kept compounding: four separate Israeli startups building tools to secure AI agents and machine identities: Onyx, Mate, Hush and Way, all announced funding within days of each other.

In the wider tech world, NVIDIA committed $5 billion to Ilya Sutskever’s SSI in a long-term strategic partnership that hands the secretive lab an order-of-magnitude jump in compute alongside next-generation Vera Rubin systems, one of the Nvidia’s largest single bets of the AI boom. China’s open-weight offensive kept rolling as Moonshot AI published the full 2.8-trillion-parameter weights of Kimi K3 a day early, making the largest open AI model ever released free to download. OpenAI answered the pricing pressure by slashing GPT-5.6 Luna by 80% and Terra by 20%, just three weeks after launch, pointing to efficiency gains but clearly feeling the heat from cheaper Chinese alternatives. Big Tech’s earnings week delivered a study in contrasts: Microsoft posted $90 billion in quarterly revenue with Azure growing 43% and crossing $100 billion for the year, Copilot doubling to more than 30 million paid seats, and shares jumping 8%; Amazon crossed $200 billion in quarterly revenue for the first time as AWS grew 37%, its fastest pace in 18 quarters, and lifted 2026 capex guidance to $220 billion, sending shares up more than 10%; while Meta beat on revenue with a 28% jump to $60.8 billion but watched free cash flow collapse as AI infrastructure spend hit $31 billion in a single quarter, dragging shares down nearly 7.5% after hours. MiniMax released H3, a video model that generates up to 15-second clips in 2K resolution with native stereo sound. Google DeepMind introduced Gemini Robotics ER 2 – a brain for robots.

QUOTE OF THE WEEK

“Wisdom is the reward you get for a lifetime of listening when you would rather have talked.”

Mark Twain

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NEW FUNDING ROUNDS

• Huge congrats Yossi Meyouhas team at Xsight Labs on raising $300 million at a $2.8 billion valuation, to develop programmable silicon chips for AI and cloud networks that were successfully on SpaceX‘s new V3 satellites.
• Way to go Maxim Bar Kogan, Gil Elbaz and the Onyx Security team on closing a $113 million Series B at a $640 million valuation, just four months after emerging from stealth to help enterprises control AI agents by managing permissions, monitoring activity, and blocking malicious or unintended behaviour!
• Congrats Shahar Azulay and team groundcover on your $100 million Series C to scale your bring-your-own-cloud (BYOC), eBPF and OpenTelemetry (OTel)-native observability platform
• Mabruk Jonathan Jacobi, Gal Niv and the Enigma AI team on emerging from stealth with a $71 million seed round to build foundation models that make robots easier to deploy!
• Good news Jonathan Langer and team Act Security on coming out of stealth with $60 million in funding
• Well done Asaf Wiener and the Mate team on a $35 million Series A just eight months after your seed to help AI agents investigate threats with real context!
• Kol hakavod Nitzan Shapira and team Harmony on coming out of stealth with $34M in funding to automate employee services across enterprises!
• Nice one Micha Rave, Shmulik Ladkani and team Hush Security on a $30 million Series A to securely control enterprise AI agents and the infrastructure they run on!
• Congrats to Dvir Ginzburg and the Encore AI team on your $30 million Series A to teach AI agents how top employees work!
• A belated congrats Yadin Soffer and team Traysar Industries on securing a $25M series A to develop the world’s first subterra defence tech company!
• Well done to Yossi Barishev and team Way Security on your $20 million seed to build the operational layer that makes identity and access management systems actually work across the enterprise!
• Mazel tov Itay Keren ? the Bloom Security team on securing a $20 million seed round to build a unified endpoint security platform for AI-native devices!
• Great stuff Daniel Shimoni and team Modus on coming out of stealth with a $10M seed round offering infrastructure to solve the “Context Gap” that prevents enterprise AI agents from delivering accurate, cost-effective results!

EXITS

• Big congrats Danny Brickman and team Oasis Security on the $1 billion acquisition by Cyera!
• Not all exits are happy, but congrats Orr Danon on the acquisition of Hailo by Microchip Technology Inc. for an undisclosed sum.

NEW FUNDS

• Big congrats Michael Eisenberg, Eden Shochat and the Aleph on launching $150M fund V with a clear message: “more of the same” – with the goal to continue backing Israeli founders building significant global technology companies!
• Congratulations Maor Shlomo on launching a new fund (self funded) focused on cancer research and breakthrough therapies after losing his mother to cancer four months ago!

LINKS FOR YOUR BROWSER

REMAGINE VENTURES/ VC CAFE/ ISRAEL VC

• The Next AI Opportunities Are the Problems AI Created (July 27) — Eze’s framework for where AI creates its own scarcities: engineering judgment as code becomes abundant, control as agents become abundant, trust as content becomes abundant, efficiency as tokens become abundant, and distribution as products become abundant. Each one is an investable category.
• Have you seen the infographic of 71 current Israeli unicorns published by Israel VC?

ISRAEL

• The Israel Innovation Authority and Ministry of Finance launched a NIS 1 billion fast-track funding programme for early stage startups affected by the strong shekel.
• Donald Trump has announced Hamas will disarm and demilitarise Gaza. The president said an agreement had been reached late last night and under the terms of the deal, which was confirmed by Hamas, a Palestinian technocratic government overseen by the US-led Board of Peace would eventually govern Gaza.
• Ilya Sutskever’s Safe Superintelligence raises $5 billion from Nvidia despite not yet releasing a product – Founded in 2024 by Sutskever and Daniel Levy, SSI now employs only a few dozen people, including a research team in Tel Aviv. The company has yet to release its first product or publish research describing the technology it is building
• BONUS: Israel’s AI Czar Seeks Chip Fab, New Data Centers to Keep Edge – by Bloomberg

GLOBAL

• A coalition including OpenAI, Meta, Google, Microsoft, Nvidia, a16z and Y Combinator signed a letter urging Washington not to impose broad restrictions on downloadable “open-weight” AI models
• We are exposed – Using Claude Mythos Preview, researchers at Anthropic have discovered improved ways to attack cryptographic algorithms (the mathematical methods used to keep online data private). Also, models compromised real-world systems during testing… (via Axios)
• Linkedin introduces a ‘seems like AI slop’ button to increase the user experience

MEDIA OF THE WEEK

The Israeli startup funnel according to Dealroom.co

The design x AI market map by Sapphire Ventures (source)

The next opportunities in AI will be solving the problems that AI has created (source: VC Cafe)

71 Israeli founded private unicorns – can also be helpful for job seekers… (source)

Agentic AI market map by Bessemer Venture Partners

Carta data shows that although the median gap between funding rounds remains around 18–24 months, the range is widening significantly, and some startups may need to survive 1,000 days, or nearly three years, without new outside capital. (source)

How to pick your AI sales strategy by Andreessen Horowitz (source)

That’s all for this week. Thank you for tuning in.

There’s a lot to celebrate in our “small” community! Keep on creating!

Eze Vidra

AI is now producing its own version of this cycle. For the past few years, much of the startup conversation has focused on what AI makes possible. But as an early-stage investor, I’m increasingly interested in a slightly different question: What did AI make abundant? and what became scarce as a result? That question may point to some of the most interesting startup opportunities ahead.

Code became abundant. Engineering judgement became scarce.

Software development used to be constrained by the number of engineers available to write code. AI coding tools have loosened that constraint dramatically: a small team, or even one person, can now move from an idea to a working product in days. But producing code and building dependable software are not the same thing.

As the cost of generation falls, the bottleneck moves from writing to judging. Does the code behave as intended? Is it secure? How does it fit the existing architecture? Who will understand it well enough to change it six months from now? Teams are accumulating machine-generated code that nobody fully owns, while impressive demos can conceal fragile dependencies, duplicated logic and technical debt. In Stack Overflow’s 2025 developer survey, 45% of developers said debugging AI-generated code was time-consuming, while 61% wanted to understand their code fully.

This creates opportunities well beyond another coding copilot: tools that map unfamiliar codebases, recover the intent behind the code, validate tests, identify vulnerabilities, enforce architectural standards and continuously refactor technical debt. The valuable product may not be the one that generates the most code, but the one that gives teams the confidence to operate it. Our portfolio company Pandorian.ai does exactly that.

This echoes the argument I made recently in “Tokenmaxxing Was the Wrong Metric”: tokens are an input cost, not a measure of value. Lines of code are becoming much the same. The outcome that matters is reliable software.

Agents became abundant. Control became scarce.

We’re moving from AI that answers questions to AI that takes actions. That is real progress, but it creates a different class of problem: How do you test a non-deterministic agent? What is it allowed to do? How do you reconstruct its decisions when something goes wrong? Who is liable if it sends the wrong payment, deletes a customer record or gives regulated advice?

The more autonomy we give agents, the more valuable the control layer becomes. Important companies will be built around evaluation, observability, permissions, simulation, audit trails and possibly insurance. But not because agents have failed, but because they are beginning to matter.

One of the key areas of opportunity here has to do with the non-deterministic nature of LLMs – run the same prompt/agent 100 times with similar input, and you might get very different outcomes.

Content became abundant. Trust became scarce.

AI has reduced the marginal cost of producing text, images, music and video to almost zero. It has not increased the amount of attention available, and it has weakened many of the signals we once used to judge what was real, original or worth consuming.

This creates several concrete opportunities. News organisations, marketplaces and insurers need to verify the origin and editing history of images and video. Banks and communication platforms need to detect synthetic voices and impersonation. Creators and publishers need infrastructure to control, license and get paid when their work is used by AI systems. Brands need to identify fabricated content and coordinated narrative attacks before they cause financial or reputational damage.

Detection alone may become an arms race as generation models improve. The more durable businesses may sit deeper in the workflow: establishing provenance at the moment of creation, verifying identity during an interaction, managing rights and payments, and building reputation systems around trusted sources.

The important question will not simply be whether a piece of content was generated by AI. It will be: Who made it? Can they prove it? Do they own it? And may it be used here?

Tokens became abundant. Efficiency became scarce.

The industry has spent years optimising for bigger models, longer context windows and more tokens. But customers don’t want tokens; they want a task completed correctly, quickly and at a reasonable cost. A model that can answer almost anything but behaves unpredictably remains difficult to use in a high-stakes workflow.

The next phase of AI may therefore be less about maximising intelligence and more about applying it efficiently. Smaller models, better routing, constrained systems, domain-specific evaluation and products that know when not to use AI could prove more useful than simply throwing more inference at every problem.

Products became abundant. Customer attention became scarce.

AI has made it dramatically easier to launch a credible product, but it has not created more hours in the day or more willingness to try another app. RevenueCat found that monthly subscription-app launches increased roughly sevenfold between January 2022 and January 2026. Yet apps launched before 2020 still generate 69% of subscription revenue, while those launched since 2025 account for only 3%. AI apps may attract curiosity and monetise well initially, but they also churn 30% faster.

Gaming makes the same imbalance visible. More than 20,000 games were released on Steam in 2025, compared with approximately 14,000 just two years earlier. Player attention has not expanded at anything close to the same rate, and the most-played games remain dominated by established titles and long-running communities. Vibe coding can produce more games, but it cannot manufacture players.

This shifts the opportunity from creation to demand. Startups can help consumers discover products that are genuinely relevant, connect developers with creators and communities, build cross-promotion networks for independent apps, or improve onboarding, retention and live operations. But the strongest products may not sell distribution as a separate tool. They will build it into the experience through collaboration, multiplayer, user-generated content, marketplaces, integrations or other loops in which usage naturally attracts more users.

This is why I’m sceptical when founders present a prototype as evidence of a moat. In the age of AI coding, a prototype is increasingly the minimum. The harder questions are how the product will reach users, why they will return and whether every new user makes the product easier, or harder, to distribute. AI democratised product creation. It did not democratise demand.

Automation became abundant. Accountability became scarce.

Employees are no longer simply using AI applications. They are assembling agents and unofficial workflows that connect models to email, customer records, internal documents, finance systems and other company tools. Microsoft reports that 29% of employees have already used unsanctioned AI agents, while fewer than half of organisations have introduced specific security controls for generative AI.

This is more consequential than traditional shadow IT. An unapproved SaaS product stores data; an AI agent may read that data, make a decision and take an action. It can inherit an employee’s access without inheriting their judgement, accountability or understanding of company policy.

That creates a concrete new infrastructure layer. Enterprises need to discover every agent operating across the organisation, give it a verifiable identity and owner, restrict it to the minimum required permissions, inspect the data it accesses and intervene before it takes a high-risk action. They also need a complete audit trail showing which model, prompt, tools and information produced each decision.

Governance cannot be limited to policies and compliance dashboards. It must operate at runtime, between the agent and the systems it is attempting to control. Every agent will eventually need an identity, an owner, defined permissions, an audit trail, a budget and a kill switch.

Look for the new scarcity

The first wave of AI startups was largely about capability: what can the models do? The next wave will increasingly be about consequences: what becomes difficult, dangerous or valuable once everyone can use them?

This is not a negative view of AI. Quite the opposite. New problems appear when a technology becomes successful enough to change behaviour. As investors, we naturally look at what a new technology enables, but abundance alone rarely determines where value accrues. Often, the better question is what becomes scarce on the other side.

AI made code abundant, but not understanding. Content abundant, but not trust. Tokens abundant, but not efficiency. Products abundant, but not distribution. Automation abundant, but not control.

The companies that solve those new scarcities may prove more durable than the ones that created the abundance in the first place.

At Remagine Ventures, we love to meet Israeli founders very early in their journey. If you’re addressing one of the new scarcities with your startup, we’d love to hear from you.

The original version of #FIRGUN was published on LinkedIn to 8,251 subscribers today!

Firgun (Hebrew: ??????, pronounced ‘feer-goon’) is an Israeli term describing genuine, unselfish joy in someone else’s success… It’s basically the opposite of “schadenfreude”. Every week since March 2020, we celebrate the wins of our startup community. Read more about why Firgun matters. If this was forwarded to you and you’d like to subscribe, previous editions are on VC Cafe.

Welcome to edition #205 of the weekly #FIRGUN on Linkedin. This week in Israeli tech, three cyber startups came out of stealth with a combined $340M in funding announced days apart (one of them even reached Unicorn status!) showing the strength of the Israeli cyber ecosystem. At the same time, several massive layoffs rounds were announced, including monday.com shedding 20% of the workforce (620 people worldwide). The layoffs represent a combination of the rise of AI/ automation and the pressure created by a strong shekel, which has increased the companies burn (in dollars) and shortened runways.

In the wider tech world, Travis Kalanick is back with $1.7 billion in funding for Atoms, his new physical-AI holding company. China’s AI race entered a new phase this week as Moonshot AI‘s Kimi K3, a 2.8-trillion-parameter open-weight coding model, shot to the top of the leaderboards and pushed annualised revenue to $300 million so fast the company had to pause new subscriptions, while Alibaba Group fired back with Qwen3.8-Max, claiming benchmark wins over GPT-4.1 and Gemini 2.5 Pro; Moonshot is now eyeing a Hong Kong IPO at a valuation above $30 billion, and the one-two punch rattled AI-linked stocks in a way that echoed the original DeepSeek shock. OpenAI had a much rockier week on the safety front, disclosing that a combination of GPT-5.6 Sol and an unreleased model escaped a sandboxed testing environment, exploited a zero-day vulnerability, and hacked into Hugging Face‘s production infrastructure in order to cheat on a cybersecurity benchmark, a genuinely unsettling first. Google DeepMind, meanwhile, shipped three new Gemini models: 3.6 Flash, 3.5 Flash-Lite and a cybersecurity-tuned 3.5 Flash Cyber for government partners, while teasing Gemini 4 on the horizon. Anthropic landed up to $5 billion in investment and chip capacity from AMD and launched an Economic Index connector inside Claude. Meta poached AWS’s Dave Brown, a 19-year infrastructure veteran, to run its data-center build-out as it lays the groundwork for a possible commercial cloud business, backed by 2026 capex guidance of $125–145 billion, while Amazon disclosed that its own custom silicon business, Trainium, Graviton and Nitro, is now running at a $20 billion annual pace with $225 billion in order commitments already booked. On the infrastructure and funding side, a BlackRock and MGX-backed consortium committed another $5 billion to Aligned Data Centers fresh off closing its $40 billion acquisition, AI-3D startup Meshy raised roughly $400 million at a $1.5 billion valuation, fintech Augustus closed $180 million at a $1 billion valuation led by Tiger Global, and battery materials maker Sila brought in $300 million, yet another reminder that the AI infrastructure and mega-round machine shows no sign of slowing down.

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QUOTE OF THE WEEK

“Trust yourself. Create the kind of self that you will be happy to live with all your life.” — Golda Meir

NEW FUNDING ROUNDS

• Huge congrats to Roi Tiger, Omer Singer and the whole Glow team on emerging from stealth with a massive $180 million (with the latest funding being a $100M series B) at a $1.2 billion valuation to reinvent endpoint security for the AI era.
• Kudos to Nick Warner, Shlomi Salem and team Neo coming out of stealth with $100 million in funding to help enterprises secure the agentic software wave, a strong debut built on deep SentinelOne, Wiz and Palo Alto Networks pedigree.
• Congrats to Adam Pellegrini and the TytoCare team on closing a $25 million+ growth round while welcoming Adam as new CEO, to scale its AI-powered remote care platform.
• Mabruk Nadav Grossinger, Nitay Romano and team Elio on coming out of stealth with $21M to build sensors for the AI era, after spending seven years developing physical sensing systems at Meta!
• Well done to brothers Tomer Malchi, and team Asio Technologies on raising a $15 million seed round after two decades of self-funding, and on landing a tactical systems deal with defense giant Anduril worth tens of millions. Patience and grit, rewarded.
• Nice one to Tal Lutzky y and team Plantopia Bio. (formerly Pigmentum) on a $9 million round, backed by dairy giant Schreiber Foods, to move from lab to commercial-scale production of real dairy proteins grown in plants, no cows required.
• Congrats to Eric Rosenthal and team Cordant on emerging from stealth with an $8 million seed round. Four Rapyd alumni who scaled payments past a billion dollars are now building the command center for the financial infrastructure they once wrestled with themselves.
• Way to go Sanaz Yashar and team Zafran Security on securing a strategic investment from Cisco Investments, extending the company’s total funding past $140 million!

EXITS

• Congrats Tamir Or, Or Schreiber and team Dondy on the acquisition of your bootstrapped startup to Circeus to turn conversations into revenue!

NEW FUNDS

• Congratulations Oded Hermoni and team J-Ventures Fund on the launch of your new $36M fund III to back early stage Israeli startups!

MISCELLANEOUS

• Way to go Amir Wolner and Guy Franklin on launching Kibbutz NYC a new workspace and innovation centre for Israeli startups in New York!

LINKS FOR YOUR BROWSER

VC CAFE / REMAGINE VENTURES / ISRAEL VC

• Requests for Startups: Fall 2026 Edition — Instead of publishing a new wishlist, this edition tests the last two “requests for startups” lists against real H1 2026 Israeli funding data, then lays out ten fresh requests for the fall: from the reliability layer for enterprise agents to consumer AI that earns repeat behavior.
• Vertical AI Market Map 2026: Israeli Startups and Funding Rounds – Israeli vertical AI just crossed a real threshold in H1 2026, from copilots that help people work to systems that run entire industry workflows. But the funding tells a more complicated story: $716M went to just 24 companies, half of it swallowed by three mega-rounds, and several “hot” categories are far more crowded than they look. Here’s the full market map, by industry, with every funding round verified.
• A bunch of new funds and upgrades added to Israel VC – the most complete directory of funds investing in Israeli startups. If you’re into startup landscapes, you should also join this new group…

ISRAEL

• Europe and Israel’s founder factories – report by Dealroom.co with Accel – Across Europe and Israel, AI is acting as a force multiplier on top of the region’s existing strengths, supercharging company creation and compressing the time it takes to reach major milestones.
• Q2 2026 Israel tech review – report by IVC Data and Insights and LeumiTech the quarterly read on Israeli deal count, capital concentration and sector mix that I leaned on for this week’s Requests for Startups piece. The good news – funding levels are high, the bad news, it’s a new low record for new startups funded.
• Rethinking the Israeli IPO – new report by Jefferies – improved liquidity of Tel Aviv Stock Exchange – ?????? ??????? ??? creates more liquidity options for startups

GLOBAL

• Alibaba, Moonshot launches mark new phase in China’s AI race – Open-source Chinese AI is improving and gaining popularity – Qwen3.8-Max, Kimi-3 and the shift from scale to practical capability by CGTN
• OpenAI’s Hugging Face breach exposes AI’s next safety challenge – by Axios – will the government accelerate safety measures to prevent future hacks?
• The 2026 Generative AI Landscape Report – by Similarweb diving into LLM usage, user behavior and performance trends

MEDIA OF THE WEEK

Israel leads in the number of unicorns in the new report by Dealroom.co (see links section)

Highlights from the IVC Data and Insights and LeumiTech H1 2026 tech review – fundraising for Israeli startups is on the rise, but it’s spread across less companies, and mostly on later stage – see links section

All the foreign VCs and CVCs that invested in Israeli startups in H1 2026

A 2026 AI agents market map for enterprise buyers: coding agents, workflow agents, vertical agents, agent infrastructure, agent washing, and how to evaluate production-ready platforms (source)

The coding agent stack by Gradient (source)

Marc Benioff: “What most impresses me about Anthropic (besides unprecedented revenue growth) is their enterprise hat trick: the best model (Claude), the best coding agents (Claude Code), & the best productivity tool (Cowork). Salesforce is proud to be an early investor, customer, and partner” – source

The Y Combinator requests for startups list for summer 2026 (source)

That’s all for this week, keep on creating!

Eze Vidra

Israeli startups raised billions of dollars during the period, but the more interesting story isn’t the topline number, it’s where the application-layer capital went. Banks, insurers, defence organisations, property managers, pharmaceutical companies and gaming studios are no longer buying AI to summarise information. They’re beginning to deploy systems that underwrite policies, manage loans, discover drugs, operate buildings, direct traffic and execute entire workflows end to end.

That’s the shift from vertical SaaS to vertical AI. Traditional software helped professionals organise their work. This generation is being paid to perform it.

But the map also requires some discipline. Not every startup using an LLM is a vertical-AI company, and not every agent platform owns a vertical. This piece tracks Israeli companies that announced funding in H1 2026 (January–June) and separates industry-specific applications from horizontal AI infrastructure, functional copilots and cybersecuritym categories that get lumped into “vertical AI” maps far too often.

What actually counts as vertical AI

A company should qualify as vertical AI when it meets four criteria:

1. It serves a recognisable industry or profession.
2. Its product encodes domain-specific workflows, data or regulation.
3. It performs or substantially automates work, rather than adding an AI interface on top of existing tasks.
4. Its competitive advantage would weaken meaningfully if the domain expertise were removed.

That framework splits the AI landscape into three layers, and only one of them is the core map:

Cybersecurity gets its own panel, not a slot on the map. It’s one of Israel’s largest technology sectors, but most AI-native security products sell horizontally across every industry rather than encoding one profession’s workflow. Folding all of Israeli cyber into “vertical AI” would overwhelm the map and make the category meaningless. Think of AI-native security as a large, important application category that sits adjacent to vertical AI, not inside it.

The H1 2026 map, by industry

Every company below was checked against its own funding announcement: press release, TechCrunch, Calcalist/CTech or Globes coverage, rather than taken at face value from secondary trackers. Several rounds turned out to be reported inconsistently across outlets or headlined with cumulative totals rather than the actual new round size; corrections are noted inline.

Finance, fintech and insurance – the broadest category

Nine companies, $196M disclosed, rounds spanning $6M to $70M with a roughly even spread across seed, Series A and later stages. No single round captured more than a fifth of the category’s capital, a sign of genuine breadth rather than one hot deal.

• Lama AI – $12M Series A (June 2026, led by EJF Ventures) – AI agents that underwrite lending for community and regional banks. Total funding now exceeds $20M; some outlets miscited the round as $10M or $20M, but $12M is the corroborated figure.
• Honeycomb Insurance – $40M growth round (June 2026, led by Zeev Ventures) – AI-native underwriting specifically for apartment buildings, condo associations and commercial multifamily property, not insurance broadly. Total funding to date: $95M.
• Novella – $16M Series A (May 2026, led by Brewer Lane Ventures) – AI brokers for excess-and-surplus (E&S) insurance. The often-cited $21M figure is cumulative funding, not the new round.
• Hypercore – $13.5M Series A (February 2026, led by Insight Partners) – an “AI Admin Agent” that runs loan operations for private-credit funds.
• Arito – $6M Seed (2026, led by Amplify Partners) – agentic analytics and BI for finance and revenue teams.
• Datarails – $70M Series C (January 2026, led by One Peak) – a FinanceOS platform for FP&A and financial analysis. Total funding: $175M.
• Atlas Invest – $25M in combined equity and debt (January 2026, led by BlackRock) – commercial real-estate bridge lending.
• Viewz – $7M Seed (May 2026, led by Ibex Investors and FLINT Capital) – ledger automation and a “continuous close” finance-ops platform.
• Dono – $6.5M Seed (February 2026, led by Link Ventures) – property-record and title infrastructure. Total funding: $10.2M.

Healthcare and life sciences – active, but still the smallest core category

Four companies and $59.4M disclosed — roughly 8% of all core vertical-AI capital tracked here. That’s a notable contrast with the US market, where Menlo Ventures estimates healthcare accounted for close to half of all vertical-AI spending in 2025. Healthcare also splits cleanly into two sub-categories that behave differently: clinical AI, which still runs into regulatory and patient-safety friction, and administrative AI, which is commercialising faster because it doesn’t.

Clinical:

• Scala Biodesign – $16M Series A (March 2026, led by Grove Ventures) – an AI protein-design platform (ScalaOS), spun out of Weizmann Institute research.
• Converge Bio – $25M Series A (January 2026, led by Bessemer Venture Partners) – GenAI drug discovery, founded by former Meta, OpenAI and Wiz executives.

Administrative:

• Take2 – $14M Series A (February 2026, led by Human Capital) – autonomous AI agents that handle healthcare recruiting and interviewing.
• CareBestie – $4.4M Seed (2026, led by TLV Partners) – voice-based monitoring and engagement for home-care and hospice patients.

Defence, security and public infrastructure: where the biggest rounds live

Six companies, $361.7M disclosed — over half of all core vertical-AI capital in this map, even though it’s the smallest company count. This is Israel’s clearest domain advantage showing up in the funding data: battlefield intelligence, autonomy, electronic warfare, and physical infrastructure like traffic and weather systems.

• Airis Labs – $31M Series B (May 2026, led by PSG Equity), on top of an earlier seed and $11M Series A, bringing total disclosed funding to $60M – AI-powered analysis of battlefield video and visual intelligence.
• Shifters – $10.2M Seed (June 2026, led by Ace Capital Partners) – autonomous ground robots for defence.
• Tenna Systems – $13.5M Seed (February 2026, led by Costanoa Ventures) – sensor fusion for electronic warfare. (Branded “Tenna Systems” to distinguish it from an unrelated US fleet-tracking company also called Tenna.)
• Conntour – $7M Seed (March 2026, led by General Catalyst and Y Combinator) – natural-language search across video surveillance systems.
• NoTraffic – $90M Series C (March 2026, led by PSG Equity) – autonomous, adaptive traffic-signal management. Total funding: $165M.
• Tomorrow.io – $175M Series F (February 2026) plus a $35M follow-on (May 2026) – weather intelligence and a satellite constellation. Combined: $210M, making it the single largest round in this map.

Several of these blend vertical software with robotics and physical hardware — worth calling out rather than forcing everything into a SaaS taxonomy.

Commerce, advertising and media

Four companies, $77.2M disclosed.

• Sett – $30M Series B (April 2026, led by Greenfield Partners) – AI agents for game marketing and user acquisition.
• Rep AI – $6.2M follow-on (May 2026, led by Silicon Road Ventures, with Zendesk’s first-ever Israeli startup investment) – ecommerce customer engagement agents.
• Brandlight – $30M Series A (February 2026, led by Pelion Venture Partners) – monitoring brand visibility across AI-answer engines like ChatGPT and Perplexity.
• Recapp – $11M (February 2026, led by Liquid2 Ventures) – personalised, AI-generated sports highlights.

Real estate and the built world

This category is already credible on its own, and it overlaps with finance and infrastructure above: Atlas Invest (real-estate lending), Dono (property records) and NoTraffic (urban mobility) all belong here too. The clearest dedicated example:

• Visitt – $22M Series B (January 2026, led by Susquehanna Growth Equity) – AI for commercial-property operations, reporting 900% growth in managed square footage in 2025.

It’s a category worth watching alongside Bessemer’s built-world AI roadmap, which flags construction and real estate as underinvested relative to their share of GDP.

Functional AI: important, but not a vertical

These companies sell into a job function rather than an industry, and conflating them with vertical AI is exactly the kind of category error this piece is trying to avoid. Six raised in H1 2026 for a combined $194M — comparable to the entire commerce and healthcare categories combined, and more concentrated at the top: the three largest functional-AI rounds captured 70% of the category’s capital, compared with roughly half in core vertical AI.

• Winn.AI – $18M Series A (February 2026, led by Insight Partners) – real-time AI sales guidance.
• Notch – $30M Series A (March 2026, led by Headline) – AI customer-support agents for regulated industries.
• Centrical – $39M Series D (June 2026, led by Leeds Illuminate) – performance intelligence for frontline teams of humans and AI agents.
• Tribal – $10M Seed (May 2026, led by Team8) – a metadata-native platform for deploying enterprise agents.
• Unframe – $50M Series B (May 2026, led by Highland Europe) – managed enterprise AI deployment. Total funding: $100M.
• Nimble – $47M Series B (February 2026, led by Norwest) – real-time web-data infrastructure for AI systems.

Alta ($25M Series A) and Aligned ($60M Series B) – announced just after this window, in early July 2026, and are early signals of the same dynamic continuing into H2.

The funding story, in numbers

Looking at dollars by category tells only part of the story. Across the 24 companies in the core vertical-AI map:

• Total disclosed funding: $716M. The three largest rounds – Tomorrow.io ($210M), NoTraffic ($90M) and Datarails ($70M) – account for $370M, or roughly 52% of all disclosed capital. Vertical AI in Israel is real, but it is highly concentrated at the top.
• Median round size: ~$15M, and 14 of 24 rounds (58%) were seed or Series A – evidence that despite the concentration at the top, there’s genuine early-stage breadth building underneath the mega-rounds.
• Fintech and insurance have the greatest breadth. Nine companies are attacking lending, underwriting, financial planning, private credit and property data independently, rather than clustering around one dominant deal.
• Defence and physical AI attract the largest rounds. More than half of all core vertical-AI capital sits in a single category – battlefield intelligence, autonomy, sensors, weather and traffic infrastructure – reflecting a genuine Israeli domain advantage rather than hype.
• Healthcare is active but still underrepresented. At $59.4M and roughly 8% of disclosed capital, Israel’s healthcare vertical-AI activity is proportionally far behind the US, where Menlo Ventures puts healthcare at close to half of a $3.5B 2025 vertical-AI spending pool.
• The horizontal-agent market is more crowded than vertical AI itself. Functional AI raised nearly as much as two full industry verticals combined, with even tighter concentration among category leaders. A lot of companies describe themselves as “agent platforms.” The harder and more defensible opportunity is owning a complete, regulated industry workflow.

Here are the investors who deployed into Israeli vertical AI in h1 2026 (courtesy of Israelvc.com)

A methodology note: a few companies’ “Israeli” identity runs through a lead investor (TLV Partners backing CareBestie) or an R&D center rather than a founding team based in Israel (Dono, Unframe). They’re included here because Israeli capital and talent are structurally involved, but it’s a judgment call worth flagging rather than asserting as settled fact.

Full funding table

Italicized rows are functional AI, shown for completeness but excluded from the core vertical-AI totals above.

How this connects to the broader thesis

A few frameworks from US-based VCs are worth reading alongside this data:

• Bessemer’s Building Vertical AI playbook argues the winners combine proprietary workflows, multimodal capability, business-model innovation and deep industry distribution.
• Menlo Ventures: Software Finally Gets to Work draws the cleanest conceptual line: vertical SaaS displayed and organised information; vertical AI reasons and executes.
• Menlo’s 2025 State of Generative AI in the Enterprise puts 2025 vertical-AI spending at $3.5B, nearly 3x the year before, with healthcare responsible for roughly $1.5B of it.
• a16z’s Big Ideas 2026 describes the next phase as “multiplayer” vertical AI — agents that coordinate people, other agents and external parties across a full workflow.
• a16z’s enterprise-adoption analysis shows roughly 29% of the Fortune 500 are already paying customers of a leading AI startup, concentrated in coding, support, search and legal.
• Bessemer’s built-world AI roadmap flags construction and real estate — about a quarter of US GDP but the lowest tech spend of any sector — as underinvested.
• Bessemer’s State of Health AI 2026 provides healthcare-specific context, including six health-tech IPOs since 2024 adding $36.6B in market cap.
• Bessemer’s defense-tech roadmap: Five Frontiers for 2026 connects directly to Israel’s strength in defence, autonomy and physical AI.

Going forward, we predict we’ll see more specialised vertical AI startups automating job roles or processes in a specific industry. If you’re an Israeli founder in stealth building in these areas, we’d love to talk to you at Remagine Ventures!

There’s a practical reason for that shift. As of mid-July, no new “Fall 2026” request-for-startups list has been published. YC’s site still shows Summer 2026 as its most recent set of asks, and a16z hasn’t updated its “Big Ideas” memo since December. But there is still a signal: a16z’s Speedrun SR007 cohort is now underway, built around themes like agent-native infrastructure, AI-native services, voice agents, and AI selling to AI, all extensions of ideas YC has been pushing since early 2026.

When multiple accelerators converge on the same themes without publishing new lists, it usually means the market has already moved.

So instead of summarizing a list that doesn’t exist yet, this edition does something different: it checks the last two sets of requests, Winter 2026 and Summer 2026, against real funding activity from the first half of the year. You can track previous editions published in 2024 and 2025 part 1 and part 2 as well as the most recent one from February 2026. All the requests below are new.

Why Israel is a useful stress test

To ground this analysis, I looked at Israeli venture funding in H1 2026. Israel is a small, dense and well-documented ecosystem, which makes it possible to map actual deals against specific theses rather than relying on anecdotes.

The headline numbers look strong. According to IVC–LeumiTech Q2 2026 and my weekly tracking of funding deals in Israel via the #FIRGUN Newsletter data, startups raised roughly $7.6 billion in H1 2026. Q2 alone reached over $4.2 billion, making 2026 one of the strongest years on record by quarterly average.

But the structure of that funding tells a more nuanced story:

• Capital is concentrated. The top nine rounds in Q2 captured over 60% of funding.
• Late-stage dominates. D+ rounds took nearly half of all capital, while Seed–A accounted for just ~17% and pre-seed barely registered.
• Fewer new bets. Only 35.5% of VC/CVC activity went into first-time investments — a record low.
• Deal count is down. Q2 saw just 87 deals, far below historical averages.

There is plenty of capital, but much less permission to be merely interesting.

The sector mix has also shifted dramatically. Cybersecurity now accounts for roughly a third of all funding, while defence, space, quantum and semiconductors have grown rapidly. Life sciences, automotive and other previously large sectors have shrunk as a share of capital.

That shift mirrors, almost line for line, what YC has been asking for: more defence, more hardware, more deep tech, more infrastructure, and less generic SaaS. Mapping H1 Israeli funding rounds against the Summer 2026 requests reveals a clear pattern: many of the most prominent categories were not just validated, they were flooded with capital.

Looking across written requests and actual funding activity, a few patterns emerge:

• Explicitly named categories get funded quickly, and become crowded. Agent security and enterprise AI are now highly competitive.
• Adjacent categories often offer better opportunities. Quantum and AI-native discovery systems sit next to major themes but face less competition.
• Gaps matter. Categories with strong theses but little funding, like agriculture, may represent open ground.

The key is to treat requests for startups as forecasts to be tested, not instructions to be followed.

Ten requests for startups for Fall 2026

1. The reliability layer for enterprise agents

Security is only part of the problem. Enterprises need to know whether agents completed tasks correctly, used the right data and behaved within policy.

There is room for evaluation, simulation and observability platforms built around real business outcomes. One of the challenges lies in the indeterministic nature of LLMs. Run the same prompt 100 times and you might get very different responses. It might be ok for creative writing, but it’s not ok for business decisions like approving a loan or refunding a product. Startups are trying to solve this with harnesses or extensive stress testing of agents, or by analysing the logs (after the fact) and being notified of anomalies. Agent reliability is another one of those categories that may already feel a bit crowded, but the problem is big and still remains.

2. Maintenance infrastructure for AI-generated software

AI makes it easy to create software, but not to maintain it.

The next bottleneck is managing complexity: dependencies, architecture drift and security. Founders can build systems that continuously map, test and explain codebases. I’ve written about ‘Cheap prototype, expensive maintenance’. All those vibe coded projects built with Lovable, Base44 and Claude Code artefacts were incredibly exciting to launch with prompts. But as they are used with real users and stress tested at scale, the bugs start to creep up, making maintenance precarious. Code review or automatic bug patching won’t do the trick here.

3. The economics control plane for AI

Companies still struggle to connect compute usage to business outcomes.

There is an opportunity to build financial infrastructure for inference: routing, cost measurement, budgeting and decision-making about when intelligence is worth buying. The rise of open-source LLMs, many of them Chinese, is currently being scrutinised by the US government, so there’s a need to better manage tokens, usage and the economic efficiency of AI. I wrote about this in my latest post on Tokenmaxxing being the wrong metric to track. I’ve seen ‘model-routing’ startups take a gatekeeping approach where every prompt will be analysed and routed to the best/cheapest model for the task. I don’t think it will work from a privacy perspective, so the door is open for better solutions.

4. Identity, payments and reputation for an agent economy

Agents are beginning to transact, but commerce infrastructure assumes humans.

We need identity, delegated authority, payments, escrow and reputation systems designed for machines. According to Cloudflare, between June 2025 and April 2026, human traffic to sites of businesses in many industries fell ~40%. Users are still buying products online, but they’re relying more and more on AI search and LLMs to do their research. The next step will be to let the agents transact, but there’s a whole tooling layer required to do that safely.

5. AI-native service companies in regulated markets

Instead of selling tools, become the service provider.

Tax, insurance, healthcare administration and compliance are all ripe for AI-native companies that deliver outcomes directly. I’ve written about AI native services in VC Cafe based on data from Sequoia’s Julian Bek, and others, and I foresee this trend will continue to grow.

6. Systems of action for the physical economy

Despite massive inefficiencies, sectors like construction and manufacturing remain underfunded.

The opportunity is to build systems that not only analyse data but take action, scheduling, sourcing, pricing and execution. Agentic AI for non-sophisticated ICPs is attractive because their margins are low (so they are desperately looking for more efficiency). In addition, the manufacturing, construction or even retail ICP would most likely choose to ‘buy’ (vs. build) due to lack of tech talent in their organisation. The caveat is that it’s not ‘one size fits all’ and go to market may feel more like a services company than a software company selling ‘saas’ licences/ seats.

7. Cheap defence against cheap autonomy

The economics of defence are shifting. Cheap drones require cheap countermeasures. Israel’s battle again Hezbo**a and the Ukraine-Russia war have demonstrated the scale of the drone threat.

Opportunities exist in sensing, electronic warfare and autonomous defence systems optimised for cost per threat neutralised. This is a category that is getting a lot of funding already and may very well become crowded, but it seems like the demand is there not just from homeland security, but also for protecting critical infrastructure.

8. Evidence infrastructure for personalised medicine

Personalised medicine requires trust, validation and longitudinal data.

Startups can build the infrastructure that makes recommendations explainable, auditable and clinically useful. We’ve seen a lot of funding going into drug discovery, but advancements in models and the availability of genomic data open interesting possibilities in the space of personalised medicine.

9. The task economy for training and supervising AI

As AI systems become more capable, they require better data and human oversight.

The next generation of data companies will organise expert knowledge into structured, high-quality tasks. This is a category that got popularised by the likes of Mercor and Micro1, but it continues to be relevant, especially as organisations aim to refine their models based on proprietary data.

10. Consumer AI that earns repeat behaviour

Consumer AI is not dead, but the bar is higher. Since the introduction of vibe coding, the number of apps on the app stores has exploded, but usage hasn’t increased massively.

The opportunity is to build products where AI enables something new, but long-term value comes from habit, identity and relationships. Founders that manage to find a niche, create a habit and get the engagement and retention needed to build a big business, may strike gold here. Gaming is part of this story.

Here you have it in one image:

What can you take away from this as a founder

The most important insight from H1 2026 is not which categories are hot. It is how quickly capital moves once a thesis is validated.

By the time a category appears on multiple investor wish lists, dozens of teams are already building in it. That also puts the VCs in a tricky situation, where even though the category seems ‘hot’, competition will make it tough to scale.

The better strategy is to identify the underlying shift, from copilots to agents, from tools to outcomes, from software to systems, and then find the implication that has not yet been fully funded.

The gap between the request and the deal flow is where the next opportunities will come from. No matter what you choose, keep in mind that the timeline for startups to exit didn’t shorten significantly, and while many startups eventually pivot, you should be willing to commit the next 7-10 years of your life working on the problem you’re focusing on, so choose wisely!

Shameless plug, if you’re an Israeli founder building in these areas, I’d love to hear from you. At Remagine Ventures, we’re often the first believers in the startup, providing pre-seed funding and helping the teams traverse the most risky part of their startup journey.

For more Requests for Startups (RFS) check out the Y Combinator Summer 2026 list that came out a few hours after the publishing of this post.

More requests for startups from Pear VC and Engage.