1 Data Extraction AI Agent, Live in Production.

A scanned invoice is a dead end for every automated process downstream of it. Duplicate detection, three-way matching, policy checks and coding all require the fields as data, and a scan has none — so a person reads the document and types the header fields and line items into a form. The keying itself is slow, and the errors it introduces are the ones hardest to catch later, because a transposed figure in a correctly-formatted field looks exactly like a correct one. Line items are the worst of it: a multi-page invoice with thirty lines is thirty opportunities, and the practical response is often to key the total and skip the detail, which removes the line-level checking entirely.

OCR Data Extractor reads a scanned invoice or receipt and pulls out the header fields and line items as structured data. Extracting the line items rather than only the header is what makes the downstream checks possible — a total alone cannot be matched against a purchase order line or tested against a spend policy. One agent covers this process, and its output is data for review rather than a posting: the extraction is a candidate, and the checks that decide whether it is right belong to the agents in Finance that consume it.