A logistics firm keyed data by hand from thousands of documents a month. We built a pipeline that reads them, checks the values, and only asks a person to look at the exceptions.
Every month, staff manually copied figures from scanned invoices and customs forms into the company's system. The formats varied by supplier and country, the work was slow, and small typing errors created real downstream problems with clearance and billing.
We built a pipeline that ingests documents in their many formats, extracts the fields that matter, and validates them against the client's existing records. Clean documents flow straight through. Anything that looks wrong or ambiguous is routed to a person, with the original and the extracted values shown side by side for a quick decision.
Because the humans now only handle exceptions, the same team processes far more volume with fewer mistakes.
We combined optical character recognition with layout aware extraction so the system understands document structure rather than just raw text. A validation layer checks each field against business rules and existing data, and a queue routes only low confidence cases for review. The whole thing runs as scheduled, monitored jobs.
"Our people used to spend their days typing. Now they review the handful of documents the system is unsure about and get on with real work. The error problems we used to chase have mostly disappeared."
Khokon Mia, Operations Manager