AI agent for sterility monitoring in pharmaceutical manufacturing

Tasks

Challenges

Solutions

• The team annotated over 7,000 cleanroom images and used targeted data augmentation and synthetic generation to simulate real-world conditions: glare, shadows, occlusions.
• Image processing pipelines were tuned to normalize lighting fluctuations before model inference, improving detection stability.
• The AI agent used a configurable rules engine to evaluate combinations of detections and escalate based on predefined risk scenarios (e.g., lack of goggles near sterile zones).
• Developed an automated logging mechanism that records all safety-related events, enabling detailed audit trails for regulatory reporting.
• Each alert included timestamped, role-specific information and direct references to SOPs, helping staff act quickly and appropriately.

Outcomes

• Deployed a real-time sterility monitoring system across the client’s manufacturing zones.
• Enabled fast, accurate detection and escalation of non-compliant procedures, reducing human oversight burden.
• Maintained target false alert rates, balancing safety and efficiency.
• Provided traceable audit logs and incident reports to support internal QA and external regulatory inspections.
• Built a scalable foundation for continuous model improvement and future expansion to additional compliance areas.

Technologies Used