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.
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.
As document and portal volumes grew, the client's reliance on manual workflows created mounting operational and compliance pressure across the business:
Fragmented Insurance Portals — Data had to be fetched manually from multiple insurer websites, each with different layouts, authentication flows, and CAPTCHA protections.
Heavy Manual Data Entry — Invoices, identity documents, and policy PDFs required manual review and transcription, slowing downstream processes.
Delayed Claims and Support Resolution — Slow document processing caused delays in claim approvals and patient assistance.
Poor Policy Understanding by End Users — Users struggled to interpret complex policy wording, driving repeated queries into support.
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.
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.
The three automation capabilities delivered measurable gains in processing speed, extraction accuracy, and support responsiveness.
Together, the three capabilities gave the client a scalable digital backbone for claims processing and patient financial services.
Faster Claim Verification — Automated document extraction and portal data retrieval accelerated the data collection stage of claims processing.
Reduced Operational Staffing Needs — Automation of portal access, document transcription, and first-line policy questions reduced dependency on manual effort and call center staff.
Improved Regulatory Compliance — Structured, standardized JSON outputs and validated extraction pipelines support more consistent, auditable data handling.
Enhanced Patient and User Experience — Instant, accurate policy answers and faster claims processing improved the experience for patients and end users.
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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