AI agent audit trail
Every decision comes with a reason. That is what makes agent operations debuggable, reviewable and defensible.
How do you audit AI agent actions?
Record every proposed action, not only the executed ones. For each decision Gatewise conceptually records the requested action, the agent, the policy evaluated, the evidence used, the decision, the reason, any approval, the execution status and the timestamp.
What gets recorded per action
- Requested action and its parameters
- Agent identity and the user or workflow it acted for
- Policy evaluated and its version
- Evidence used, with source and freshness
- Decision and the reason for it
- Approval, including who approved and when
- Execution status returned by the business system
- Timestamp
Three audiences, one record
- Operations: why did the agent not send that message?
- Compliance: show that the approval rule was applied every time
- Engineering: debug an agent that keeps proposing blocked actions
Blocked actions matter most
Executed actions usually leave a trace in the target system. Proposed and blocked actions do not, and they are the ones that tell you where your agents are drifting.
Questions
Frequently asked questions
Give your agents freedom without giving them a blank cheque.
Tell us what your agents are allowed to do today. We will review whether Gatewise fits your agent workflow.
Works with your agents and existing business tools