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Designing OCR around the review workflow

Document automation works best when extraction, business validation and human review are designed together.

Build a representative sample

Collect the document types, layouts and scan conditions the process actually receives. Define which fields matter and prepare reviewed reference values. Keep evaluation samples separate from configuration work so the team can assess whether the solution handles new inputs.

Assess business usefulness, not only recognition

A field may look plausible while being unsuitable for the next process. Add checks for required values, valid dates, reference records and consistent totals where the workflow needs them. Track both extraction errors and the effort needed to correct them.

Make uncertain results easy to review

Show the source document beside extracted values. Route exceptions to the right role and make corrections traceable. Users need a clear way to reject a document, supply missing information or return it for clarification before it enters downstream systems.

Expand only after the workflow is dependable

Pilot one bounded document process and compare handling effort, review workload and error patterns with the existing approach. Record changes in input quality or document layouts during operation. Extend to additional document types when the review process and acceptance criteria are understood.

Before you start

  1. Representative documents and reviewed reference values

  2. Field-level and business-level validation

  3. A usable review and correction flow

  4. Measured handling effort and expansion criteria

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