An extraction workflow can reduce rekeying while leaving uncertain fields with a reviewer. Start with one document family and a clear target record. Decide which errors can be corrected later and which fields need a human check before any downstream action.
Build a field dictionary
List every required field, its allowed format, where it appears, and what to do if it is absent. Separate a value read from the document from a value inferred using reference data. Include several layouts, poor scans, and unusual but valid examples in the test set. Keep the source document available to reviewers.
Design the review queue
Route low-confidence fields, inconsistent totals, unknown identifiers, and unreadable pages to a person. Show the relevant source excerpt and the proposed value together. Keep changes traceable so a corrected record can be checked later. Decide when a whole document needs review instead of one field.
Measure misses and watch for drift
Compare accepted values with an agreed set of checked examples. Record both incorrect accepted values and items that were sent to review unnecessarily. Inspect changes in the mix of document layouts and the volume of corrections. Add a newly encountered layout to the test set before broadening coverage.
Example
Send a supplier form with a missing reference to a reviewer before any record is created.
What to do next
Use extraction results as a proposed record when errors could affect a payment, a customer record, or another important decision.