OCR pipelines for document-heavy industries

The 80% that pays for itself

In travel and operations, staff spend hours retyping data off documents. An OCR pipeline can remove most of that. We have cut manual entry by ~80%, but only if you design for the messy 20%.

Pipeline shape

1. Ingest: normalize the image (deskew, denoise).
2. Extract: OCR (Tesseract or a cloud API) into raw text + bounding boxes.
3. Structure: an LLM pass maps raw text to your schema.
4. Score: every field gets a confidence value.
5. Review: anything below threshold goes to a human queue.

Don't skip confidence scoring

The difference between a useful pipeline and a liability is the confidence gate. High-confidence fields flow straight through; low-confidence ones are flagged, never silently trusted.