Your developers run the same AI coding agent dozens of times a day. A secret one session reads gets parked in a file, and a later session picks it up and ships it out. AgentSaw follows the value across every session and agent on the dev's machine, and catches the handoff no single tool can see.
Endpoint, prompt firewalls, DLP. Even the agent-security tool you may have just bought. None of them is built to follow a value across your coding agents. Here's why each walks right past it.
Each tool watches one session, or one agent, and calls it clean. The leak only appears when you connect all of them, which is the one thing none of them does. And no, standardizing on one agent doesn't help: your devs run that one tool all day, and the leak lives between sessions.
AgentSaw tags a sensitive value the moment a session reads it, then follows that exact value across every session, agent and tool, even after it's copied, logged or moved between files, and acts before it lands somewhere it shouldn't.
The moment an agent reads a secret or sensitive value, AgentSaw marks it at the source: .env, a vault, a customer record.
It traces that exact value as agents copy, log and transform it, across every session, in Claude Code, Cursor, Cline and Codex.
When a later session moves the same value toward a risky destination, AgentSaw recognizes it, no matter which agent is holding it now.
One clear alert on the cross-session timeline. Turn on blocking and it stops the action before the value reaches a wiki, a PR or a public doc.
AgentSaw connects through each agent's own hook and extension APIs and reads the tool calls they make (file reads, shell commands, network requests) right on the developer's machine. It watches what your agents do, not just what's in their prompts.
Every catch is one leak that didn't ship: a value read in one session, recognized when a later session moved it toward an internal wiki or a customer email.
Example data — your number depends on how your team runs agents. A healthy week trends toward zero, and each catch comes with the full cross-session story behind it.
AgentSaw is local-first by design: the watching, the tagging and the decisions all happen on the developer's machine. The dashboard runs in your network and works from redacted events — never raw values.
AgentSaw reads the agents' tool calls through their own hook APIs, tags sensitive values and follows them — all locally, in an encrypted local store. Raw secrets never leave the laptop.
Secrets stay hereRuns in your network. It receives redacted events — the movement, the sessions, the destinations — and builds the timeline and alerts your team works from.
No raw valuesWe're working hands-on with a small group of AI-native teams who run AI coding agents every day. Local-first: almost nothing to approve, so you can have it watching in an afternoon. You get the cross-session timeline and a direct line to the founders; we get your feedback.