How Israeli startups build with AI — the capability mix from agents to vision, foundation-model build-vs-buy, the infrastructure and security layers, and where it is all applied. Proprietary signals from the startupim corpus, read against external market data and the voices of the ecosystem.
AI is no longer just a sector of the Israeli startup ecosystem — it is a layer running through nearly half of it. This report measures that layer from the technologies companies declare and the code they ship (the startupim corpus and radar), and sets those proprietary signals against external market data and the people shaping the ecosystem.
Five findings frame the year. (1) Scale, two ways to count it. In our broad “applies-AI” classification, 5,802 companies — 44% of the corpus — carry an AI signal; external trackers using a stricter “AI-native” bar put it nearer a quarter to a third, but agree on the money: AI startups capture roughly 47% of all Israeli tech funding (Startup Nation Central, 2025). (2) The agentic turn is real and corroborated. Agents are the fastest-rising capability in our data, and Remagine Ventures independently finds 52% of new GenAI startups now claim agentic capability (CTech, Jul 2025). (3) Buy the model, build the system. Almost no Israeli company trains its own foundation model; the strategy is to orchestrate hosted intelligence — a posture even Israel's own national-strategy committee now accepts. (4) The edge is one layer up from the model: AI security and AI infrastructure, where Israel's cyber DNA compounds — AI-security funding alone reached ~$2.5B in 2025, 64% of all cyber investment (CTech/SNC). (5) Applied everywhere — AI concentrates in business software and health but is material across agriculture, industry, fintech and defense.
The through-line, in the words of Yonatan Mandelbaum of TLV Partners:
Of 13,152 active companies in our corpus, 5,802 carry an AI or machine-learning signal — 44%. That number is higher than external trackers report, and the gap is instructive: it is a question of definition, not of disagreement.
classifications.technologies (Artificial Intelligence / Machine Learning), AI primary sector, or AI tags.Reconciling the count. Our 44% is a deliberately broad “applies AI” union. External trackers measuring “AI-native” companies land lower: Startup Nation Central describes “more than 2,300 AI startups… roughly one quarter of tech companies,” while other industry counts put it above 30% (SNC). Both can be true — the difference is whether a company that uses AI in a vertical product counts as an “AI company.” Where the sources converge is on capital: AI startups draw ~47% of all funding and ~40% of rounds, and AI-startup funding rose from $4.9B in 2024 to ~$7.9B in 2025 (+61%) (CTech, citing SNC). However it is counted, AI is where the money is.
Reading each company's own description of what it builds, we counted the distinct AI capabilities named. Descriptions are terse, so these are conservative floors — but their relative order is the signal, and it matches what independent landscape research is reporting.
about / one_liner / seo.about, June 2026. Counts are floors (terse descriptions undercount); read the ranking, not the absolute values.Two stories sit in this chart. The first is continuity: computer vision and machine learning remain the ecosystem's deepest AI competencies — a legacy of Israel's strength in sensing, autonomous systems, medical imaging and defense. The second is the agentic turn: AI agents have vaulted to third (356 companies) and clearly lead the older chatbot paradigm (94). This is not just our reading — Remagine Ventures' Israeli GenAI Landscape 4.0 counts 342 generative-AI startups and finds that 104 of the 198 founded since May 2024 (52%) claim agentic-AI capability (CTech, Jul 2025).
Note how few companies claim to train their own foundation model (8) or even mention fine-tuning (18). The named exemplars of the new cohort are agent companies — Alta (an “AI revenue workforce” of sales agents), Notch (agents automating insurance and finance workflows) and Wonderful (enterprise agents; $150M Series B at a $2B valuation within a year of founding). As Mandelbaum frames it, “the bottleneck is now agents.”
For the 684 AI companies with a matched public GitHub organisation, the radar code signal confirms the build stack — and the wider data shows these teams are themselves now built around AI coding tools.
| Signal | Companies | Share | Reading |
|---|---|---|---|
| Python in public repos | 265 | 39% | model / data lingua franca |
| Jupyter Notebook present | 51 | 7% | research in the open |
| Repo themed “model / ML / inference” | 132 | — | core modelling work |
| Repo themed “vision / image / detect” | 130 | — | vision lineage, in code |
| Repo themed “agent” | 98 | — | agent frameworks & demos |
| Repo themed “chat / bot / conversational” | 86 | — | conversational interfaces |
| Repo themed “LLM / GPT / RAG” | 54 | — | LLM-native tooling |
sources.github joined to AI-classified companies, June 2026. Repo-theme counts tally companies whose top public repos match the theme; a company can match several.The repo themes mirror the capability mix almost exactly — model and vision repos lead, with a fast-growing agent cohort (98 companies) now out-publishing classic chat repos. And the engineers writing this code are unusually AI-augmented: the Israel Innovation Authority reports that 95% of Israeli high-tech employees use AI tools regularly (78% daily) and 74% of younger technical staff use code-oriented tools such as Copilot and Cursor (a joint Israel Innovation Authority / Startup Nation Central survey, 2025). By the same data, Israel ranks among the highest countries globally in Anthropic Claude usage per working-age person.
Assembling the signals into the canonical AI stack shows a clear pattern: Israeli startups are thin at the foundation-model layer and thick everywhere a vertical product, an agent, an infrastructure pick-and-shovel, or a security control can be built. External funding data corroborates each layer.
The two layers where Israel's existing strengths compound are infrastructure and security. On infrastructure, capital is flowing into the “AI supply chain” — Nebius alone is deploying 4,000 Nvidia B200 GPUs and 80 MW of Israeli data-centre capacity (CTech). On security, Israel's cyber lineage has produced the defining companies of the AI-security category: Cyera ($600M at a $12B valuation in 2026), Prompt Security (acquired by SentinelOne) and Aim Security — and AI-security is now 64% of all Israeli cyber investment, up from 34% a year earlier. The model layer, by contrast, is a deliberate non-bet.
The “buy the model, build the system” posture is now national policy, but it arrived through genuine debate about whether Israel should build a sovereign model at all.
Israel approved a National AI Program (the directorate established September 2025, a broader package in June 2026), budgeted at roughly NIS 1 billion to date and moved into the Prime Minister's Office, with pillars in talent, sovereign compute, energy and regulatory acceleration (CTech; National AI Program, official PDF). The government's own Nagel Committee was blunt that Israel is “far behind” the hundreds of billions major powers are deploying — and questioned whether a sovereign Hebrew LLM is even feasible, given Hebrew lacks the corpus scale to train a frontier model from scratch, suggesting fine-tuning an existing model instead (INSS).
The bull case. Agents keep compounding (already past chatbots in our data and the majority of new GenAI startups); the infrastructure layer thickens as GPU and data-centre capacity lands locally; and AI security graduates from feature to category, carried by Israel's cyber DNA. H1 2026 reinforced it: Israeli startups raised roughly $8.6B, up ~45% YoY, led by AI, cyber and enterprise software (CTech / Ynet).
The bear case, which the data also supports. 2025 set funding records on a decade-low 717 deals, with half of all capital in $100M+ rounds — the ecosystem is narrowing onto a few high-conviction security and AI fields, raising concentration and bubble concerns echoed globally (CTech / SNC annual report). Avi Hasson, CEO of Startup Nation Central, frames the year not as a return to normal but as “a pivot toward high-conviction maturity” — a description that contains both the optimism and the risk.
For builders, the strategic reading is consistent across our data and the external voices: own the system, not the model; compete on the agent, infrastructure, security and vertical layers; and treat proprietary data and Israel's engineering density — first in the world for AI-talent concentration — as the moat.