AI-enabled quality, deviation, and CAPA management for regulated manufacturing
An AI quality platform that detects and prioritizes deviations, suggests confidence-scored root causes, tracks CAPA effectiveness, and keeps an inspection-ready record.
- Client
- A regulated manufacturer (anonymized)
- Techniques
The problem - A regulated manufacturer had no consistent way to manage deviations, spot recurring root causes, or prove CAPA effectiveness across sites. Issues were handled reactively, and demonstrating effectiveness to an inspector meant assembling records after the fact.
What we built - An AI quality-management platform that runs the full deviation lifecycle: it detects and classifies deviations across manufacturing and lab data (Critical, Major, Minor), recommends likely root causes with confidence scores drawn from historical and cross-site patterns, and links CAPAs to deviations to flag potentially ineffective actions when an issue recurs. Site-scoped role controls, preventive-action analytics, document exports, and a seven-year audit trail.
The outcome - Turns deviation management from reactive paperwork into a proactive, cross-site view with an audit-ready record - designed to sit alongside validated systems, not disrupt them.