Structure the event
Extract product, process, symptom, location and immediate context from the approved record.
Retrieve similar events, identify evidence gaps and prepare review-ready investigation material—without allowing AI to declare root cause, approve disposition or close CAPA.
Open the controlled demo ↗The agent supports the repetitive work around an investigation. The customer’s quality process and system of record remain authoritative.
Extract product, process, symptom, location and immediate context from the approved record.
Find potentially related NCRs, CAPAs, complaints or supplier events with direct source links.
Highlight missing measurements, records, people, samples or tests needed for investigation.
Draft a problem statement, investigation plan and testable hypotheses for review.
The accountable user accepts, edits or rejects the preparation material.
Every output is designed around an agreed source boundary and a named approval point.
Relevant history, recurrence links and previous action with source references.
Missing information organised for the investigation owner.
Problem statement, investigation plan and clearly labelled hypotheses.
Baseline comparison, user acceptance, limitations and scaling recommendation.
Choose based on data readiness and operational risk—not ambition alone.
Up to 250 historical records from CSV or Excel, one site, one workflow and up to five users. No production integration.
One connected source, up to 1,000 records, up to ten users, monitoring, training and a customer-reviewed production recommendation.
Autonomous root-cause declaration, product disposition, CAPA approval or closure, product release, QMS replacement, regulatory certification and unscoped enterprise migration.
Use the free value call to test event volume, investigation effort, data readiness and the governance boundary.