Manual transcription of handwritten field notes and delivery receipts creates a critical data latency and error bottleneck, delaying lot traceability, impeding FSMA 204 compliance, and obscuring real-time inventory quality. A custom automation workflow uses specialized computer vision and LLM agents to extract structured data—lot IDs, weights, origins, temperatures—directly from images or scans. This transforms a 48-hour manual process into minutes, enabling immediate posting to ERP systems like SAP or Oracle and providing the real-time data foundation for downstream spoilage prediction and recall execution.




