Document Intelligence Review

Contractual field-level accuracy SLAs hold vendors accountable where marketing claims do not.

Polling architecture and silent failures make Azure Document Intelligence unreliable for production.

Evaluate document platforms by portability and accuracy separately, not together.

Accurate field extraction from payslips requires layout-agnostic parsing and arithmetic validation.

Organizations can escape document AI lock-in by owning data and testing exit paths early.

How to safely replace document understanding while keeping OCR and managing vendor risk.

Ask vendors to back accuracy claims with service-level agreements tied to your actual documents.

Clean data at ingestion prevents hallucinations that prompt engineering alone cannot fix.

Silent wrongness on systematic document classes costs more than crashes ever will.

Dedicated preprocessing APIs catch parsing errors that corrupt retrieval.