Every extracted value should lead back to its source.

An invoice, a statement and company articles describe different objects. The task needs to specify whether it seeks an amount with its currency, a reporting period, a full legal name or a role held on a particular date. A collection of recognised words is not enough to populate a case safely. The output should preserve meaningful units and avoid silently converting an absent field into a zero.

Character recognition may help read an image, while a model may suggest a structure. Both can fail on tables, missing pages or a poor scan. The design needs to distinguish a value explicitly present in the document from an inference and from missing information. A fluent explanation must not conceal that the source does not support the proposed answer.

The proposed workflow associates each field with an identified document and a checkable passage. A review interface could place the page alongside the extracted value and make returning to the original straightforward. The reference should remain meaningful after a correction or a later document version. A page number and exact passage are more useful than a general assertion that a document was checked.

Checks depend on the material: a valid date format, the direction of a transaction, preserved currencies or conflicting totals. These can flag inconsistencies, but they do not establish authenticity. An apparently high confidence score needs evaluation before anyone relies on it. Uncertainty and unanswered fields should remain visible even when the rest of the extraction looks complete and well formatted.

An evaluation should compare fields against expected answers defined beforehand. Synthetic material can cover clear documents alongside tilted scans, blank cells and ambiguous digits. Correct values, wrong values and abstentions need separate counts. Returning fewer answers may be preferable to filling gaps with invented information. No universal performance figure is meaningful for document formats that have not yet been examined.

The time needed to review the proposal matters as much as extraction accuracy. A useful comparison considers manual entry, source-assisted review and correction of difficult cases. A change to the model, its instructions or page splitting can alter the result and should be tested again. The assessment should also reveal where keeping a manual step is the more dependable choice.

An export needs to distinguish proposed and reviewed values, identify the source and explain how a correction reaches the receiving tool. Repeated imports should not create another copy of the same record. The interface available in an accounting or case system determines what can be preserved; a spreadsheet with no source reference may lose the very evidence that made extraction useful.

Document handling includes more than the original file: page images, extracted fields and technical logs also need appropriate access and retention settings. A useful handover explains how to find the source of a value, correct it and export the reviewed result without losing that connection. The organisation chooses who may open the original and who only needs the prepared information. Recognising a name or number remains distinct from verifying an identity or accepting a client.