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AI-Powered Insurance Automation, OCR Document Extraction, and Policy Chatbot Solution Delivering 70%+ Faster Processing and 95%+ Extraction Accuracy

MoreYeahs built an integrated automation suite for a healthcare and insurance technology platform, combining insurer portal automation, OCR-based document extraction, and an LLM-powered policy chatbot, cutting document processing time by more than 70% while reaching 95%+ extraction accuracy.

Nov 1, 2025
Published
MoreYeahs
Author
Healthcare
Tags
Overview
  • Industry: Healthcare & Insurance Technology
  • Engagement: AI Automation, OCR Document Intelligence & Conversational AI
  • Focus: Insurance Portal Automation, Invoice/ID Document Extraction & Policy Chatbot
Objectives
  • Client - Healthcare & Insurance Technology domain
  • Automate data collection from multiple insurance company portals
  • Build scalable OCR-based document extraction APIs for invoices and identity documents
  • Enable real-time, LLM-powered policy question answering for end users
01 / 07

Customer

The client is a digital health and insurance technology platform supporting claims processing, policy administration, and patient financial services.

Its operations depend on high volumes of documents and third-party insurer portals for claims, policy validation, and patient support, workflows that had historically required significant manual effort across data entry, document review, and customer service.

02 / 07

Business Challenge

As document and portal volumes grew, the client's reliance on manual workflows created mounting operational and compliance pressure across the business:

01

Fragmented Insurance Portals: Data had to be fetched manually from multiple insurer websites, each with different layouts, authentication flows, and CAPTCHA protections.

02

Heavy Manual Data Entry: Invoices, identity documents, and policy PDFs required manual review and transcription, slowing downstream processes.

03

Delayed Claims and Support Resolution: Slow document processing caused delays in claim approvals and patient assistance.

04

Poor Policy Understanding by End Users: Users struggled to interpret complex policy wording, driving repeated queries into support.

03 / 07

Solution

MoreYeahs delivered three connected automation capabilities spanning portal data collection, document intelligence, and conversational policy support.

Insurance Portal Automation: Browser automation scripts log into multiple insurer portals, handle CAPTCHA-protected and dynamically rendered pages, and fetch structured data on a scheduled basis for centralized storage.

OCR Invoice & Identity Document Extraction API: A FastAPI-based service parses Aadhaar cards, PAN cards, insurance policy PDFs, and hospital invoices, combining OCR with regex validation, positional text detection, and NLP-based context extraction.

LLM-Powered Policy Chatbot: A retrieval-augmented generation (RAG) chatbot answers policy questions directly from ingested policy documents, reducing reliance on human-staffed support channels.

04 / 07

Implementation

Each capability was engineered around the specific technical challenges of its document type or portal, then validated before integration into existing workflows.

Portal Resilience: Headless Chrome sessions with session persistence and retry logic maintain reliable, scheduled data synchronization across insurer portals with varying layouts and authentication flows.

Document-Specific Extraction Pipelines: Aadhaar and PAN extraction combine OCR with regex- and format-based validation, while insurance policy and hospital invoice extraction use layout-aware OCR, PDF parsing, and NLP-based field mapping for policy metadata, cost fields, and diagnosis and service codes.

RAG Chatbot Pipeline: Policy PDFs are ingested, chunked, and embedded, then served through vector retrieval and prompt-engineered LLM responses behind a JWT-secured API layer.

Validation & Testing: Portal automation stability testing, OCR accuracy benchmarking against clean and edge-case scans, and LLM response relevance checks were run before rollout, alongside load testing on API endpoints.

05 / 07

Technology

Portal Automation: Selenium-based browser automation with headless Chrome sessions.OCR & Document Processing: Tesseract OCR, EasyOCR, PDFPlumber, Pillow, spaCy, and regex-based validation.API & Data Layer: FastAPI services with Pydantic schema validation for standardized JSON outputs.Conversational AI: PyMuPDF for PDF parsing, LangChain for chunking, and Google Gemini Pro for RAG-based response generation, secured via JWT-based API endpoints.
06 / 07

Results

The three automation capabilities delivered measurable gains in processing speed, extraction accuracy, and support responsiveness.

4
Production-Ready APIs
95%+
Extraction Accuracy
70%+
Faster Processing
2
3 Second Chatbot Response Time
Automated Portal Data Retrieval: Insurance portal automation eliminated manual login and data-collection effort across multiple insurer sites, with reliable scheduled synchronization.
07 / 07

Business Impact

Together, the three capabilities gave the client a scalable digital backbone for claims processing and patient financial services.

01

Faster Claim Verification: Automated document extraction and portal data retrieval accelerated the data collection stage of claims processing.

02

Reduced Operational Staffing Needs: Automation of portal access, document transcription, and first-line policy questions reduced dependency on manual effort and call center staff.

03

Improved Regulatory Compliance: Structured, standardized JSON outputs and validated extraction pipelines support more consistent, auditable data handling.

04

Enhanced Patient and User Experience: Instant, accurate policy answers and faster claims processing improved the experience for patients and end users.

05

Scalable Automation Foundation: The API-driven architecture establishes a foundation for extending automation to additional insurers, document types, and support channels.

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