Intelligent Document Processing

A great deal of business-critical information still arrives as a scan, a fax, or a PDF built from a photograph. Somebody reads each one and types its contents into a system, and the volume means the work is never finished and the errors are never fully caught.

Extraction tools promise to solve this and then fail in the most damaging way available: by being confidently wrong on the documents that differ from the samples, with no signal that anything went wrong.

This concept build demonstrates extraction designed around its own uncertainty. Every extracted field carries a confidence score, and the threshold for automatic acceptance is set per field according to the cost of getting it wrong - an invoice total is held to a far stricter standard than a reference note.

Anything below threshold goes to a review queue where a person sees the extracted value beside the highlighted region of the source document. Confirming or correcting takes seconds, and corrections feed back into the labeled set.

Accuracy is measured against that labeled set per document type and per field, so the reported figure is specific rather than a single marketing number. Documents the system has not seen a template for are identified as unknown rather than processed on a guess.