Evaluate representative samples first
Document layout, image quality, handwriting and language affect extraction results. We identify the required fields and decide how missing or uncertain values should be flagged. Instead of promising an accuracy percentage, we review results from a representative sample set and use those findings to define the scope.
Keep review and export explicit
OCR output should not be assumed correct. A review interface, field validation and retry steps let a person compare values with the source document. Approved information can be exported to Excel or passed to an existing application where agreed. Critical fields need their own checking rules.
Consider privacy and running costs
If a third-party AI service is used, the information sent to it must be identified beforehand. Sensitive content, access roles and retention requirements are discussed as part of the project. Volume, document length and provider pricing affect running costs. Bring sample documents and an approximate monthly volume to the first discussion so we can evaluate a suitable workflow.