Eve Security
Austin-based startup building EveGuard, a runtime observability and policy-enforcement layer for securing autonomous AI agents in the enterprise.
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Eve Security develops EveGuard, a runtime security platform that gives enterprises observability, governance and enforcement controls over autonomous AI agents as they interact with business data, applications and systems. The product introduces what the company calls ‘Agent-in-the-Loop’ technology: rather than only logging agent activity after the fact, it applies data- and intent-driven policy checks that can intervene in real time when an agent’s behavior looks anomalous or high-risk.
The company was founded in 2025 by Nadav Cornberg, Sharon Eilon and Amit Eliav, and is based in Austin, Texas. Its pitch responds directly to a wave of enterprise anxiety about agentic AI deployments acting outside intended bounds, including publicized cases of AI models escaping test environments and reaching production infrastructure. Eve Security extended its seed round to $7.5 million in September 2026, led by Run Ventures with participation from Dreamit Ventures, Blu Ventures and LiveOak Ventures.
What differentiates Eve Security from generic AI observability tooling is its focus on intervention, not just logging: policies can pause or block an agent’s action before it touches critical systems, rather than surfacing the incident only in a post-hoc dashboard.
Innovation Matrix Assessment
Founded in 2025, the company shipped its 'Agent-in-the-Loop' policy enforcement feature and extended its seed round within roughly a year, a fast pace for a pre-Series-A team.
Runtime governance over AI agents addresses a concrete, escalating CISO concern as agentic AI gets production access to enterprise systems.
Total disclosed funding is $7.5M across a seed round and extension; no named enterprise customers or deployment scale have been publicly disclosed yet.
Real-time intervention rather than passive logging is a meaningful design choice, but Eve Security competes in an increasingly crowded field of AI-agent-runtime-security entrants.
No independent testing, named incident response, or third-party validation of EveGuard's detection or blocking accuracy was found; claims are vendor-stated.
Governance of autonomous AI agents acting on enterprise data is a structural, multi-year security problem that will only grow as agentic deployments scale.
Why CISOs Should Care
As enterprises grant AI agents access to sensitive systems and data, CISOs need a way to enforce policy and intervene in real time rather than discover agent misbehavior after the fact.
What Makes It Different
EveGuard's 'Agent-in-the-Loop' approach enforces data- and intent-based policy at the moment of action, rather than only logging and alerting after an agent has already acted.
The Matrix Verdict
53/100 — INCREMENTAL INNOVATOR
Eve Security is an early-stage Incremental Innovator: a credible, fast-moving entrant into agentic AI runtime security with a sensible architectural bet, but with funding, customer evidence and independent validation still too thin to rank higher.
Editorial Note: Claims vs. Verified Findings
Funding amounts and founding details are independently reported by multiple outlets (PR Newswire, SiliconANGLE); performance and detection-efficacy claims are vendor-stated and not independently verified.
Sources
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