On July 20, 2026, a company called Neo emerged from stealth with $100 million in backing from Andreessen Horowitz and Bessemer Venture Partners. The founders are Nicholas Warner, Shlomi Salem, and Eran Shirazi — veterans of SentinelOne, Wiz, and Palo Alto Networks. Their pitch is simple: enterprises are adding AI agents faster than they can track them, and existing security tools were never designed for software that makes decisions on its own.

That gap is real. Gartner projects that 40% of enterprise applications will have embedded AI agents by the end of 2026, up from less than 5% in 2025. That’s a near-eightfold jump in one year. Every one of those agents is a new attack surface, a new data access point, and a new accountability question that most security teams are not equipped to answer.

What Neo Actually Builds

Neo describes itself as an “Agentic Software Control” company. The core product gives security operations teams four things:

Inventory — a real-time view of every AI agent, AI-enabled app, autonomous browser, and agentic identity running across the enterprise. Most organizations deploying agents today have no complete list of what they’ve shipped.

Posture intelligence — continuous assessment of how those agents are configured, what data they can access, and whether those configurations match policy.

Attribution — when an agent takes an action, who or what approved it, and why. This matters enormously for regulated industries where every consequential decision needs an audit trail.

Policy control — enforceable rules that govern what agents can and cannot do, applied consistently across cloud environments, vendors, and endpoints.

Craft Ventures and Merlin Ventures also participated in the round alongside the lead investors from a16z and Bessemer.

Why This Problem Is Getting Worse, Fast

Traditional security tools were built for human users and known software. You could enumerate your applications, set up user access controls, and monitor network traffic. AI agents behave differently: they run continuously, chain tools together, browse the web, write code, send emails, and access APIs — all without a human approving each step.

The risk is not theoretical. Shadow AI agents are already appearing in enterprises the same way shadow IT did in the early cloud era. A developer spins up an agent connected to the CRM. A finance team deploys an automation that reads and writes to a database. Neither shows up on any security dashboard.

What makes this particularly hard to manage is that the agent landscape is fragmented. Some agents are custom-built. Others come pre-packaged in SaaS products. Others are deployed by contractors through tools like Claude Code or Codex. A single enterprise might have dozens of these running, each with different permissions and different data access.

Neo’s bet is that this chaos needs a dedicated control layer, not just a feature bolted onto existing SIEM or endpoint tools.

What This Means for Business

If you’re a business owner thinking about AI agents — or already deploying them — this funding round is worth paying attention to for two reasons.

First, it confirms that enterprise AI governance is not optional anymore. The capital flowing into companies like Neo reflects what sophisticated buyers are demanding: visibility and control over automated decision-making before it becomes a compliance or reputational problem.

Second, it signals where the AI market is maturing. We’re past the phase where deploying an AI agent is the news. The industry is now working out what it means to govern those agents at scale, and the tools to do that are arriving.

For businesses evaluating AI deployments, the practical implication is this: don’t wait for a breach or an audit finding to start thinking about governance. The questions are worth asking now — what agents are running, what data do they access, and who is accountable when they make a mistake.

That conversation is as much about business operations as it is about security. If your AI agents are touching customer data, financial systems, or internal communications, governance is not a technical concern. It is a business concern.

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Enterprise DNA’s Omni services help businesses deploy AI agents with structure — defined scope, clear handoffs, and accountable outcomes. If you’re evaluating what agentic AI looks like in your business before it becomes a problem to manage, start with a discovery call.