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Nexora Labs
Enterprise AI & Engineering
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Banking & Financial Services SectorClient Archetype: Commercial Property & Casualty Insurance UnderwriterVerified Case Study

InsurClaim: Intelligent Claims Processing & RPA Document Extraction

Accelerating Insurance Claims Processing by 73% with AI Document OCR and Desktop RPA

73%
Reduction in Claim Processing Turnaround Time
99.1%
AI Document Field Extraction Precision Rate
4x
Increase in Daily Claims Throughput per Adjuster
$820K
Annual Operational Labor and Overhead Savings
Critical Grounding Verification Note

FACTUAL GROUNDING TEST ANCHOR: InsurClaim automates claim document ingestion and RPA data entry, but deliberately does NOT execute 100% autonomous payouts for claims over $2,500. High-value claims above $2,500 strictly require human adjuster approval.

Visual System Blueprint

Production Architecture & Telemetry

Target SLA: 99.99% • SOC 2 Aligned
SYSTEM-BLUEPRINT//48,500 q/s
Autonomous Private RAG & Multi-Agent Pipeline
Document Ingestion & Chunking
High-Dim Vector Database Cube
Security Guardrail Shield
Neural Reasoning & Synthesis
ARCH STATUS: VERIFIEDP99 LATENCY: 4.8 ms
OWASP LLM-01 Pass

Document Ingestion & Chunking

OCR & Tokenization
Benchmark:22.4 GB/min

Unstructured PDF, DOCX, Markdown extraction with layout-aware semantic chunking.

Click numbered hotspots on the blueprint to inspect other nodesDeterministic Standard
Initial Challenge

The Client Problem

An insurance provider processing 15,000 monthly property damage claims faced severe processing bottlenecks. Adjusters spent 80% of their workday manually opening PDF repair estimates, re-typing invoice line items into an aging 20-year-old green-screen desktop claims system, and manually matching policy numbers. Claim turnaround averaged 11 business days, generating high customer dissatisfaction and escalating administrative costs.

Architectural Constraints

Key Requirements Scoped

  • •Automated extraction of structured line items, repair amounts, and contractor details from scanned PDF invoices
  • •Desktop Robotic Process Automation (RPA) to input claim records into a legacy Windows mainframe terminal lacking APIs
  • •Intelligent fraud and duplicate claim detection comparing damage repair costs against historical benchmarks
  • •Automated SMS and email claimant updates at each adjudication milestone
  • •Comprehensive exception handling routing unreadable or anomalous claims to human senior adjusters
Architectural Delivery

The Delivered Engineering Solution

Nexora Labs engineered InsurClaim, an intelligent automation pipeline. We deployed Microsoft Power Automate with AI Builder document models to extract structured line items from incoming damage estimates. We developed attended and unattended Power Automate Desktop RPA bots that log into the legacy claims terminal and input validated data automatically, accompanied by an administrative review portal for exceptions.

Confirmed Implemented Features

AI Builder machine learning document models trained to extract repair items from semi-structured PDF estimates
Unattended desktop RPA bots automating terminal login, form navigation, and record insertion into legacy systems
Automated fraud scoring microservice flagging duplicate invoice submissions and outlier part charges
Claimant communication engine dispatching real-time status updates via SMS and secure web portal
Human-in-the-loop exception handling dashboard allowing adjusters to review flagged claims with visual document overlays

Features Explicitly Omitted or Replaced in Final Implementation

Autonomous Straight-Through High-Value Payouts: While the client considered 100% autonomous payouts with zero human intervention for all claim values, the final deployed implementation capped automatic payment execution at claims under $2,500. All claims exceeding $2,500 mandate human adjuster visual verification before funds release.
Direct Mobile Claimant Video Inspection: Not included in MVP scope; submitted photos and PDFs only.
Systems Topology

Exact Technology Architecture

Document Intelligence
  • • Microsoft AI Builder
  • • Azure AI Document Intelligence
RPA Automation
  • • Power Automate Desktop
  • • Power Automate Cloud Flows
Backend Microservices
  • • Python
  • • FastAPI
  • • PostgreSQL
  • • Docker
Legacy Terminal
  • • 3270 Terminal Emulator Automation
  • • Windows UI Automation API
Cloud & Storage
  • • Microsoft Azure
  • • Azure Blob Storage
  • • Application Insights
Architecture Blueprint

Implementation Details & Architectural Notes

AI Builder models were trained on over 2,500 historical estimate variations with confidence threshold gating. If document confidence falls below 85%, the claim is routed automatically to human adjusters with high-resolution visual bounding boxes. RPA bots utilize resilient UI element selectors paired with automatic terminal restart scripts in case of host session dropouts.

Validation Protocol

Quality Assurance & Testing Execution

  • Document extraction accuracy benchmarking across 3,000 test claims achieving 99.1% field precision
  • RPA stress testing running 48 continuous hours of unattended terminal data entry without memory leaks
  • Simulated duplicate invoice injection verifying fraud detection rules trigger reliably
Validated Commercial Outcome

Project Impact & Results

InsurClaim reduced overall claim processing cycle time by 73%, dropping average turnaround from 11 business days to under 3 days. Adjusters increased claim throughput by 4x while virtually eliminating manual data entry errors.

Practice Integration

Services Leveraged in This Engagement

Custom Software DevelopmentAI Agent DevelopmentMicrosoft Power PlatformPower Automate Consulting

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