AI agents now plan, decide, and act on their own. They call tools, query databases, chain actions across systems — all at machine speed, under delegated human credentials.
The security infrastructure protecting your enterprise was designed for a world where software does exactly what it's told. That world is ending.
Your IAM layer can authenticate an agent and hand it a set of permissions. That part works. What it can't do is evaluate whether the agent's next action makes sense — whether it fits the task, whether the data it's touching is appropriate, whether the sequence of calls it's chaining together is heading somewhere dangerous.
An agent built to query one database schema has credentials to read everything its owner can. A coding assistant with repo access can exfiltrate secrets through a tool call that looks routine. A support bot that reads customer records accumulates a dataset across a session that no single query would have revealed.
The attack surface isn't the agent's code. It's the identity it was handed and the autonomy it was given.
Every existing approach — gateways that enforce per-call policy, identity platforms that manage credentials, discovery tools that inventory what's running — addresses a fragment. None of them operate where it matters: at the point where the model decides what to do next, before any tool is ever invoked.
We think governance has to live where intent forms — not where actions land. That's what we're building.
We believe the right architecture watches the full lifecycle of an agent session — from the moment intent forms through every tool call, data access, and downstream action. Not after the fact. Not per-call. The entire trajectory.
Every agent, every tool, every identity chain — governed and ungoverned alike.
Learn what normal looks like for each role and context. Flag what doesn't fit.
Data flowing through agent context is a surface nobody's watching yet.
Individual calls look fine. The trajectory is where threats compose.
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