Production Record Compliance

With global drug production outsourcing surging to 60%, Pharma organizations face a critical challenge: manual compliance oversight of shared PDF batch records from CDMOs. These records—ranging from Electronic Batch Record (EBR) outputs to handwritten scans—create a "compliance blind spot" where manual oversight is effort-intensive and often misses scribal errors, data gaps, and GMP non-compliances.

Zipp.ai is a validated AI solution for automated compliance monitoring of vendor-shared batch records. Unlike traditional systems requiring full digital integration, this tool ingests PDF records (digital or scanned) to autonomously audit for GMP compliance and ALCOA+ standards. We demonstrate how AI ensures CPPs and CQAs alignment, verifies data consistency, and detects anomalies across typed values, handwritten entries, and missing signatures, effectively bridging the gap between siloed vendor systems and internal quality standards.

Case study results show a significant reduction in review effort and "Cost of Poor Quality" (COPQ) by catching non-compliances early. This approach enables proactive oversight of the external supply chain, replacing reactive manual checks with Review by Exception (RBE) approach for both internal and outsourced production.