Continuous GxP audit-trail review. Read-only by design.
ATR evaluates nine standard compliance use cases against every audit event in your QMS — every cycle. We connect read-only, so we cannot corrupt what we cannot modify. Subscription, not a project.
Sampling and spreadsheets can't keep up with modern QMS volumes.
QA leaders inherit thousands of audit events per week — and review a single-digit percentage by hand. When a regulator pulls the sample you didn't review, the finding is permanent. ATR evaluates every event, every cycle, with the same scoring rubric.
Manual review = blind spots
Sampling 5–10% of audit events guarantees that 90–95% of activity is never reviewed. Findings appear later in inspection prep — too late to remediate.
Headcount doesn't scale
Hiring more reviewers compounds inconsistency. Two analysts looking at the same trail apply different rubrics.
Findings without evidence
When a manual reviewer flags something, the audit trail of the audit is itself a fragile spreadsheet. ATR's findings are cryptographically chained to source events.
Encoded judgement. Applied uniformly.
Each check is its own versioned AI agent, tested against a curated set of examples and double-checked every run. Add a tenth check at any time — every deployment of ATR picks it up on the next cycle.
Unauthorised data change
Detect modifications to GxP records made outside the change-control process.
Backdated record creation
Flag entries whose created_at timestamp predates the event they purport to record.
After-hours / weekend activity
Surface user-driven changes outside standard operating hours.
Privileged-user actions on regulated data
Audit every action taken by system admins against records under change control.
Reason-for-change missing or boilerplate
Identify records where the change reason is blank, generic, or copy-pasted.
Identity / sign-off mismatch
Catch sign-offs where the approver is the same person as the author or is not authorised.
Out-of-sequence workflow transitions
Detect state transitions that skip required steps in the SOP-defined workflow.
Anomalous bulk operations
Statistical anomaly detection on the volume and shape of recent changes per user.
Records linked to known-failed equipment
Cross-reference change events to equipment with active deviations or CAPAs.
A platform behind every finding.
ATR is not a pile of regex. Each compliance check is a versioned AI agent, double-checked before any finding reaches your QA team — and every result chains back to the source event.
Every check is screened against the patterns we have seen break AI agents before — so they cannot break yours.
Each finding is scored on a confidence band. Green flows straight to QA, amber escalates, red is blocked outright.
Every finding chains to the previous one. The whole audit-of-the-audit is cryptographically traceable.
Before the AI queries your data, the platform checks the question against your real vocabulary. Hallucinated references are rejected before they touch your records.
If the data feed lags, ATR refuses to guess. The agent abstains and surfaces the gap rather than making a finding on stale records.
Five sensitivity tiers, with attribute-based access control. Sensitive findings only route to reviewers who are cleared to see them.
Be audit-ready every day, not just before inspection.
ATR runs continuously, surfaces findings to a QA queue, and chains every finding to a hash-linked evidence pack. Pull the report at any time — for any regulator, any time-window.