Case study
Turning a paper mountain into structured, searchable intelligence.
We built a document intelligence pipeline that classified, extracted, and routed a multi-million-document backlog in weeks, not years.
A federal agency held a two-million-document backlog of mixed scans, forms, and correspondence — each requiring manual classification and data entry. We deployed an OCR-plus-LLM pipeline that classifies document type, extracts fields with confidence scores, and routes low-confidence cases to humans. Everything runs inside their accredited environment with full audit trails.
What we deliver
- Document classification across hundreds of form types
- Field extraction with per-field confidence scoring
- Human-in-the-loop review for low-confidence cases
- Full audit trail inside an accredited environment
Outcomes
Backlog cleared
Two million documents processed in weeks instead of years.
Accuracy held
Extraction accuracy exceeded the prior manual baseline.
Staff redeployed
Data-entry staff moved to higher-value casework.
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