Insurance
Claim Amount Forecasting
Client
RMS
Industry
Healthcare
Services
Workflow Automation
Duration
Enterprise Grade
Executive Summary
Engineering resilience through RMS's transformation.
Claims were submitted in diverse, unstructured formats requiring massive manual effort. The provider needed an end-to-end system that integrated advanced OCR with AI-driven analysis. Clearleaff implemented an Insurance Case Analysis Agent using LlamaParse for contextual extraction from handwritten notes and low-quality scans.
Optimizing Claim Analysis
- Extract information from unstructured claim formats.
- Maintain data integrity with precise OCR processing.
- Scale claim handling with automated analysis agents.
- Integrate decision support from parsing to evaluation.
The Intelligent Parsing Solution
- Implemented AI-powered Insurance Case Analysis Agent.
- Used LlamaParse for advanced OCR and contextual extraction.
- Enabled real-time, asynchronous scalable document parsing.
- Delivered features for adequacy and similar case search.
Measurable Outcomes
Measurable Impact
75%
Processing Speed Increase
2x
Capacity Growth
100%
Client Satisfaction
Faster Processing & Scalable Document Parsing
Claim handling time reduced from 40 mins to just 10 mins, achieving a 2x increase in processing capacity without losing accuracy. The solution provided fully automated decision support for complex medical cases.
Technical Stack
Tesseract OCRLangChainPostgreSQLDjango RestLlamaParse
Core Disciplines
OCRInsurTechAutomation
