Specify the output before the model
List the exact fields your business needs and how each will be used. An invoice number, currency and due date need different checks. Decide which document types are supported and how multi-page files should be grouped. This prevents a demo with a few clean samples from becoming an undefined production process.
Keep the source close to the result
A reviewer should be able to compare an extracted value with the document it came from. Show missing fields and failed validation clearly. Where practical, preserve page references or highlighted source regions. Avoid making staff search an entire file to understand one questionable value.
Separate extraction from approval
Do not treat a neatly formatted output as permission to update a financial or operational system. Check required fields, reconcile totals where applicable and detect repeated documents. Route uncertain cases to a person. The relevant standard is whether the record is usable for the business decision, not whether the extraction looks plausible.
Measure the review effort
Track the corrections reviewers make, the document types that fail and the time required to approve a record. Use a representative sample, including scans and incomplete files, when assessing the workflow. Expand the supported scope only when the team can explain how errors are caught and corrected.
Put the idea to work
Document & data processing
Extract, validate and organize information from documents and emails, with review queues for incomplete or uncertain results.
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