A mid-sized insurance organization was seeing claim volumes rise while its claims adjudication process remained heavily manual.
Analysts had to review PDFs and handwritten claims documents, extract relevant information, map benefits, calculate payouts, and determine which claims required additional review. The organization needed a way to absorb increased volume without adding staff, while also introducing AI-driven document matching and decision-support capabilities that its internal IT team did not yet have in-house.
An AI claims-adjudication workflow that turns PDFs and handwritten documents into structured data, matches them to policy benefits, scores confidence, and routes low-confidence or edge cases to human reviewers.
Tasks that previously took 40-45 minutes were fully automated or reduced to about 10-12 minutes.
The team moved from a high-level business goal to a functioning prototype fast enough to validate feasibility and build stakeholder confidence early.
After proving value in the initial accident expense workflow, the solution expanded into additional insurance claim types and higher-complexity use cases.
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