AI Audit

"What did the AI do, and was it allowed?" Have the answer.

An immutable, tamper-evident record of every AI action — initiating user, agent, model, tools, MCP, policy outcome and timestamp. Filter it, investigate it, export it to your SIEM.

Every other system in your enterprise keeps a log. Your AI — the one acting autonomously, touching data, making decisions — too often does not. So when a customer disputes an action, a regulator opens an inquiry, or data ends up where it shouldn't, you're left reconstructing what happened from memory. Autonomous AI without an audit trail isn't a productivity tool; it's an unbounded liability.

The problem: AI is a black box you can't investigate

An agent took an action. Which user was it acting for? Which model and tools did it use? Did a policy allow it, or did it slip through? Without a unified record, those questions have no answer — and "we're not sure what the AI did" is the worst sentence to say to a regulator, a customer, or your own board.

Why it matters to the enterprise

Audit is where accountability becomes real. It's what lets your SOC investigate an incident, your compliance team produce evidence, and your legal team answer "on whose behalf?" with certainty. It's also the connective tissue to the tools you already run: piping AI activity into your SIEM means your AI estate stops being a security blind spot and becomes part of the same monitoring as everything else.

If you can't explain what your AI did after the fact, you can't be accountable for it. Audit is what makes autonomous AI defensible.

How AuthSpoke does it

One timeline for the whole estate

Because every capability — agents, models, tools, policies, sessions — writes to the same event stream, Audit is a single, coherent timeline of your AI estate, not a dozen disconnected logs you have to stitch together.

What you get

Make every AI action accountable

Keep an immutable trail of what your AI does — and turn "we're not sure" into a query you can answer in seconds.