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AI Agent Audit Trail

The short answer

A good trail lets anyone reconstruct each step: what the agent saw, what it did, which rule or model output decided it, what changed in the system, who approved, and when. Capture it per step, protect it from edits, keep secrets out, and keep it as long as the business record it supports.

Why a log line is not proof

An auditor asks four things: what happened, who did it, on what basis, and can you prove it. "Invoice 44817 processed" answers none of them. A chat transcript records what a model said, not what the system did.

  • What?missingWhat it did
  • Who?missingWho
  • Why?missingWhy it decided
  • Proof?missingSeal

Record every step

The step is the right unit. A run can have forty steps, and the one that went wrong needs its own record.

FieldWhat to capture
Step identity Workflow and version, run ID, step number
Time and place Timestamp with time zone, machine, session
What it saw The screenshot or page it read, and the region used
Values read Each value and where it sat in the source
Why it decided Rule name and version, or model output and what routed it
What it did Target control, typed text (masked if sensitive)
What changed The screen after, plus the system's response
Outcome Success, failure, retries, escalation
Who The agent, the user session, any approver
Seal A hash of this record and the one before

Three more records

Steps alone are not enough.

Run record

What triggered it, the batch, counts of completed, escalated and failed items, duration.

Change record

Every edit to a workflow, rule, table or model, with who, when, old value and new value. A wrong number next quarter usually traces to a change made this quarter.

Review record

Who reviewed, what they saw, their decision, any correction, the reason code, how long it waited.

What never goes in the log

  • Passwords, session IDs, tokens and keys
  • One-time codes, even though they flash on screen
  • Bank, card and sensitive personal data in screenshots (mask at capture, not later)
  • A model's free-form reasoning text (store the output, the decision and a short reason)

Proving nobody edited it

A log in a shared folder is a document anyone could change. Hash chaining fixes that cheaply. Each record stores a fingerprint of itself plus the fingerprint of the record before it. Change one screenshot and the chain breaks from that point on.

Export the evidence in a format an auditor can open without the vendor's software, and keep a copy operators cannot alter.

How long to keep it

The trail inherits the retention of the record it supports. Use the longest rule that applies: tax rules, contract audit clauses, regulators, or your own records policy.

Tier storage to keep it affordable: full screenshots for a recent window, then extracted values and hashes. Keep full images indefinitely for anything that failed or went to review.

Storage estimate

0GB per month at full resolution

After 12 months: 0 GB keeping every image, 0 GB tiered.

full screenshots (recent window) extracted values and hashes

Assumes about 2 KB of values and hashes per step after the window. Items that failed or went to review keep full images and are not included.

How LaunchAI handles it

Every action, decision and run in LaunchAI is logged with screenshots, kept on the machine that did the work, and exportable in an audit-friendly format. Credentials and one-time codes stay out of the record. Product →

Questions

Is a screenshot trail sensitive data itself?

Yes. It holds whatever the agent saw. Encrypt it, restrict viewing by role, log who opens it, and apply the same retention as the source records.

How is this different from the ERP's change log?

The ERP log shows that a field changed and under which user. It cannot show what the agent was looking at, which rule decided, or who approved outside the ERP. An investigation needs both.

No prompts. No babysitting. No Integrations.

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