AI Document Intelligence for Claims Processing
A production document intelligence pipeline that reads insurance claim PDFs and scans with OCR and an LLM, auto-processing 71% of claims end to end and cutting average handling time from 22 minutes to 3.
01The Challenge
A third-party insurance administrator received claims as PDFs, faxes, and phone-camera photos, and adjusters keyed more than 40 fields per claim into the policy system by hand. At 22 minutes per claim the team could not keep pace with intake, and a multi-week backlog was pushing the administrator past its contractual turnaround times.
02The Solution
We built a pipeline that runs every inbound document through OCR, extracts the structured claim fields with an LLM, and attaches a confidence score to each individual field. Claims where every field clears the threshold post straight to the policy system, while anything uncertain routes to a human review queue with the low-confidence fields highlighted against the source page. A separate evaluation harness replays 5,000 labeled historical claims on each model or prompt change so per-field accuracy and drift are measured before anything reaches production.
Tech Stack
Key Deliverables
- OCR + LLM extraction of 40+ structured fields from PDFs and scans
- Field-level confidence scoring with a human review queue
- Evaluation harness over 5,000 labeled claims tracking accuracy & drift
Business Impact
"Cut average claim handling time from 22 minutes to 3, auto-processed 71% of claims with no human touch at 98.4% field-level accuracy on the evaluation set, and cleared the entire backlog within 5 weeks of go-live."
Figures shown are representative of typical engagement outcomes. Individual results vary with scope, data quality, and existing systems.
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