OCR turns an image into text, but it does not guarantee that the number, name, or date is correct. Hebrew documents with stamps, handwriting, and tables need a process that shows the source beside...
OCR turns an image into text, but it does not guarantee that the number, name, or date is correct. Hebrew documents with stamps, handwriting, and tables need a process that shows the source beside the extracted value. Automation hiding uncertainty creates silent errors.
Define which fields may be extracted, which require verification, and what sends a record to exceptions: low confidence, unusual amount, existing document number, or missing required field. Retain original text in a protected file and record which model or rule produced the value.
Measure accuracy by document type and supplier, not one successful demo. If the document contains personal information, assess minimisation, permissions, and provider agreement before upload. OCR is an intake step, not accounting or legal approval.
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Yehonatan Saadia
Freelance automation, web & MVP developer
I'm Yehonatan Saadia, a senior developer who builds business automation, custom websites, and MVPs for small and mid-sized companies across the US, Europe, and Israel. These guides come from real client work, not theory.
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