Every operations team that receives documents from outside the company ends up with the same workflow: a shared inbox, a folder of PDFs, and a person who opens each one and types values into an ERP, a spreadsheet or an internal tool. The work is slow, it does not scale with volume, and it produces inconsistencies that are expensive to unwind — a vendor name spelled three ways, a tax field left blank, a total that does not match its line items.
The usual response is to buy an OCR tool. That solves the easy half of the problem. Raw text extraction leaves the hard half untouched: deciding which of the extracted values can be trusted, what to do when a document type is unfamiliar, how a reviewer sees the original document next to what the machine read, and how the business proves later why a value was accepted.
The gap is not recognition accuracy. It is the absence of a workflow around uncertainty. Without one, teams either trust everything the model returns, or check everything by hand and lose the benefit entirely.