Thousands of scanned documents. OCR over originals of terrible quality. Classification and extraction over corpora that cannot leave the jurisdiction under professional secrecy.
That is a heavy documentary inference load under a data residency constraint.
It is the reason we evaluate local inference: the work to be done does not fit in an API call that leaves the jurisdiction. It is not a stance, it is what the material requires.
Volume
Thousands of documents per book, not dozens. Cost and latency stop being a detail.
Quality of the original
OCR over old scans, stamps, handwriting and copies of copies.
Egress constraint
Corpora covered by professional secrecy that cannot leave the jurisdiction.
Immutable trail
The record is append-only: it is not rewritten, it is chained.
Timestamping
Each check is dated at the moment it happened, not when it was looked up.
Chain of custody
Which document was seen, which source it came from, and who approved it.
Reproducibility
Being able to reconstruct afterwards why the system said what it said.
The diagnosis measures how you gather, check and archive today, and which part of that can or cannot leave.
Keep exploring BiVelio
Sibling pages that dig into the same topic from a different angle. Useful to see how BPM, automation, AI and real cases fit together.