Case study · AI · 2026
AI document intelligence for a logistics operator
Thousands of shipment documents processed automatically, every day.
LLMPythonAWSPostgreSQL
The problem
A mid-sized logistics operator processed thousands of bills of lading, customs forms, and invoices every day. Clerks re-keyed data by hand, errors slipped into downstream billing, and peak days backed up the queue for hours.
The solution
We built a document intelligence pipeline combining OCR, layout-aware extraction, and LLM validation against existing ERP records. A human-in-the-loop review screen handled only the uncertain cases.
The result
Document processing time dropped from minutes to seconds, extraction accuracy reached 98.7%, and the operations team was redeployed to exception handling instead of data entry.