Linx Security
AI-native identity security platform that discovers, scores, and helps remediate risk across both human and non-human identities.
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Linx Security builds an AI-native identity security platform that discovers, maps, and governs both human and non-human identities across an organization’s cloud, SaaS, on-prem, and custom applications. The platform constructs an identity graph that connects accounts, entitlements, and access relationships, then uses that graph to score risk, flag anomalous or excessive access, and surface gaps that traditional identity governance and administration (IGA) tools tend to miss, particularly around service accounts, API keys, and other machine identities.
Founded in 2023 in Tel Aviv by CEO Israel Duanis (previously of Check Point Software) and CPO Niv Goldenberg (previously of Transmit Security and Adallom), Linx emerged from stealth in mid-2024 with a $33 million combined seed and Series A round led by Index Ventures and Cyberstarts, with angel backing from Wiz founders Assaf Rappaport and Yinon Costica. The company has since closed a $50 million Series B, giving it substantial runway to build out automation and remediation workflows on top of its identity graph.
The company’s pitch centers on closing the gap between finding identity risk and fixing it: rather than just reporting on excessive entitlements or stale accounts, Linx aims to automate remediation and access-review workflows directly. That focus on non-human and AI-agent identity sprawl – a fast-growing blind spot as organizations deploy more service accounts, API integrations, and autonomous agents – is a differentiator versus legacy IGA vendors built primarily around human workforce access.
Innovation Matrix Assessment
In roughly two years, Linx moved from stealth to a multi-module platform covering identity intelligence and analytics, automation and remediation, and an AI copilot, a fast release cadence for a company this young.
Founders came from Check Point, Transmit Security, and Adallom, and the round included Wiz's founders as angels, but the company is still early: no public customer count or logo list is available to gauge operational scale.
Linx raised a combined $33M seed and Series A in 2024 led by Index Ventures and Cyberstarts, then closed a $50M Series B, a rapid and well-backed capital trajectory for a two-year-old company.
Building an identity graph that treats human, non-human, and AI-agent identities as one governed population, with a focus on automated remediation rather than just reporting, differs meaningfully from legacy IGA tools built around periodic human access reviews.
No named enterprise customers, third-party evaluations, or documented incident outcomes are publicly available yet; efficacy is currently supported mainly by investor and founder pedigree rather than independent proof.
Non-human and AI-agent identity sprawl is one of the fastest-growing categories of enterprise risk, and closing the gap between identity visibility and actual remediation is a top-of-mind problem for identity and security teams.
Why CISOs Should Care
Gives identity and security teams a single, continuously updated map of human and machine access relationships, with automation aimed at actually closing excessive-access gaps rather than just flagging them.
What Makes It Different
Treats non-human and AI-agent identities as first-class citizens of the identity graph alongside human accounts, and emphasizes automated remediation workflows over static reporting.
The Matrix Verdict
65/100 — INCREMENTAL INNOVATOR
A well-funded, well-pedigreed early-stage entrant addressing a genuinely underserved problem (non-human identity governance); promising on paper, but independent proof of real-world efficacy is still thin.
Editorial Note: Claims vs. Verified Findings
Funding amounts and investor names are independently reported by multiple outlets (Times of Israel, CTech, SiliconANGLE, Index Ventures). Platform capability claims (identity graph accuracy, automation effectiveness) come from company materials and are not yet backed by named customer case studies or third-party benchmarks.
Sources
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