Agent governance runtime
Policy checks that run before an AI agent acts, and an audit record of what it did, on whose authority, and with what inputs.
Request early accessThe problem
An agent with tool access can send the email, update the record or move the money before anyone looks. Most teams find out what happened from logs written for debugging, not for an auditor.
When risk or compliance asks who approved an action, the honest answer is usually that nobody did.
How it works
Write the policy
State which agents may call which tools, with what limits, and which actions need a person to approve them.
Check before the action
Each proposed action is evaluated against policy before it runs. It is allowed, blocked, or held for approval.
Record the decision
Every action is written to an audit record: what the agent did, on whose authority, with what inputs, and which rule applied.
Answer the question later
When someone asks why the agent did something, you look it up instead of reconstructing it.
Who it is for
- Platform teams putting agents into production workflows
- Risk, compliance and audit teams who have to approve them
- CIOs who want agents in production without an open-ended liability