80% fewer manual claims.
100% audit trail.

A Document Intelligence and Workflow Intelligence deployment. End-to-end OPD and IPD reimbursement claim processing.

PP-StructureV3NuExtractPolicy EngineHITL queuePostgreSQL

CLIENT CONTEXT

A large government healthcare reimbursement body processing hundreds of claims per day across a complex policy landscape with differing rate tables, eligibility criteria, and approval flows.

THE PROBLEM

Every claim arrived as a scanned bundle — prescriptions, bills, test reports, policy documents. Officers spent hours per claim on extraction, eligibility checks, duplicate detection, and rate validation. The backlog kept growing.

How We Approached It

Four phases.
Each one auditable.

01

Intake and extraction

Scanned bundles ingested, OCR-processed, classified by document type. Structured fields extracted at temperature 0.0 for deterministic output.

02

Policy validation

Extracted fields cross-referenced against rate tables, eligibility criteria, duplicate detection. Clear cases routed for auto-approval.

03

HITL review

Low-confidence cases queued for human officer review with original documents alongside extracted fields. One-click approve or override.

04

Audit and reporting

Every decision logged with reasoning, hash-chained. Monthly reports on spend, approval rates, exception patterns generated automatically.

80% fewer manual claims.100% audit trail.

Four phases.Each one auditable.

Your case study next.

80% fewer manual claims.
100% audit trail.

Four phases.
Each one auditable.