Automation Insurance NGO LangChain Azure Form Recognizer Power Automate

Intelligent Document Processing Workflow

This workflow shows how document-heavy teams can move from manual review to structured intake, classification, extraction and routing. It is designed for claims, reports, applications and compliance files that need consistent handling.

92%
Straight-through rate
500+
Docs processed / day
<1hr
Routing SLA (was 2 days)
4โ†’1
Team headcount shift
โš  Before
4-person team manually reviewing and routing incoming documents. 2-day SLA. High error rate on data extraction. Staff bottleneck during peak intake periods.
โœ“ After
92% of routine documents processed straight-through with no human touch. Same-hour routing. Team of 1 handles exceptions only. Error rate reduced from 12% to under 2%.
๐Ÿ”’
Use cases below are representative, not client-specific. Specific client names, document schemas, and system integrations are protected under non-disclosure agreements. Scenarios reflect real-world patterns across multiple sector engagements and are presented as transferable use cases.

Where this applies

Insurance
Claims Document Intake
Automatically extract policy numbers, dates, and damage descriptions from unstructured claim submissions and route to the right adjuster queue.
NGO / Government
Field Report Processing
Classify and route incoming field reports, extracting key indicators and flagging items needing human review from high-volume humanitarian operations.
Legal / Compliance
Contract Abstraction
Extract key clauses, dates, and obligations from contracts at volume for compliance tracking registers โ€” without a legal team reading every document.

Processing Architecture

๐Ÿ“จ
Document Intake
โ†’
๐Ÿ”
OCR / Form Recognizer
โ†’
๐Ÿง 
LLM Extraction
โ†’
๐Ÿท๏ธ
Classification & Validation
โ†’
๐Ÿ“ฌ
Auto-Route / Escalate
โ†’
๐Ÿ—ƒ๏ธ
Record & Archive

Problem Statement

When documents arrive in many formats, staff spend too much time reading, sorting and re-keying information. This project demonstrates how a document workflow can reduce that manual load while keeping human review in the loop.

Scale consideration: At 500 documents/day, even a 5-minute average handling time per document represents over 40 person-hours of routine processing daily. Automating the routine 92% frees your specialists for the 8% that genuinely requires human judgement.