American-Israeli cybersecurity startup Neo emerged from stealth mode on Monday with $100 million in seed and Series A funding, unveiling a platform that gives enterprises real-time control over AI agents, AI-enabled applications, and traditional software. The investment round, backed by Andreessen Horowitz, Bessemer Venture Partners, Craft Ventures, and Merlin Ventures, signals surging demand for security solutions purpose-built for the agentic AI era.
Neo’s $100M Funding Round and Market Entry
Neo will deploy the capital to scale its engineering and go-to-market teams as it moves to establish a foothold in the rapidly emerging category of AI security and governance. The company’s platform functions as a centralized control layer that sits between an organization’s software stack and its security operations, providing unified visibility into every active element across the enterprise environment.
How Neo’s Platform Controls and Secures Enterprise AI
Security operations teams using Neo can maintain a continuous, real-time catalog of active elements, including AI agents, models, extensions, and MCP servers. The system automatically evaluates these discovered assets to identify excessive access privileges and configuration vulnerabilities that could be exploited by adversaries.
A core capability of the platform is its real-time attribution engine, which traces every individual software action back to the originating human user, automated agent, or specific application identity. This allows security teams to enforce granular policies governing tool calls, data movement, agentic workflows, and API access. When unauthorized activities are detected, the system can automatically restrict them or pause suspicious operations for manual review, providing a safety valve for high-risk actions.
What does Neo’s platform do? It provides enterprises with a unified control layer that continuously discovers, catalogs, and governs AI agents and AI-enabled applications, enforcing granular security policies based on real-time attribution of actions to specific users, agents, or application identities.
Founding Team and Industry Experience
Neo was founded by Nick Warner, Shlomi Salem, and Eran Shirazi. Warner, who serves as CEO, previously held leadership roles including president and COO at SentinelOne, as well as senior positions at Cylance, McAfee, and Forepoint. Salem, the company’s CPO, led detection engineering at SentinelOne, while Shirazi, the CTO, co-founded customer experience firm EasySend. The combined experience in endpoint security, detection engineering, and enterprise software positions the team to address the complex challenges of AI governance.
The Growing Imperative for Agentic AI Security
AI agents and agentic capabilities are being embedded into browsers, developer tools, SaaS platforms, and traditional applications at an accelerating pace. These systems can reason, act, invoke external tools, and move through complex workflows while operating with valid user permissions. This creates a fundamentally new attack surface that traditional security tools were not designed to address. Warner noted that Neo gives enterprises the real-time control layer they need to understand what agentic software can do, govern how it behaves, and secure adoption without slowing down the business.
What Enterprises Should Do Now for AI Governance
As AI adoption accelerates across every industry sector, security teams should immediately evaluate their ability to discover, monitor, and govern AI agents and AI-enabled applications operating within their environments. Implementing a dedicated control layer that provides real-time visibility, attribution, and granular policy enforcement for agentic software represents a prudent and necessary step toward managing the risks associated with this rapidly evolving technology category. Organizations should assess whether their existing security infrastructure can address the unique challenges posed by AI agents that operate with autonomous decision-making capabilities and valid user credentials, and begin planning for dedicated governance solutions that can keep pace with the speed of AI adoption.
