Language models catch OCR errors that rule-based tools miss, but they introduce new failure modes.
Confidence scores route OCR extractions, but only if thresholds match the document type and risk.
Regulated document workflows need extraction systems that prove their work, not just get it right.
Most extraction tools fail silently on complex tables until reconciliation reveals the damage.
Document structure beats arbitrary token limits for better retrieval results.
Test OCR tools on your actual documents before deployment, not vendor benchmarks.
