AI-powered document processing system
Created an intelligent document extraction pipeline using computer vision and LLMs to automate data entry workflows.
Client
Insurance Company
Industry
Insurance
Duration
3 months
Impact
95% reduction in manual data entry
The Challenge
The insurance company processed thousands of claim documents monthly (medical records, bills, police reports, photos). Data entry staff spent 80% of their time manually transcribing information from documents into systems. This created delays in claim processing and high labor costs.
Our Solution
Built an end-to-end document processing pipeline that handles diverse document types (PDFs, images, handwritten forms).
Implemented computer vision models to extract text, tables, and key data points from structured and unstructured documents.
Used LLMs to understand context, classify document types, and extract entities (names, dates, amounts, policy numbers).
Created confidence scoring system that auto-processes high-confidence extractions and routes low-confidence cases for human review.
Built a human-in-the-loop interface for reviewing and correcting AI extractions, with feedback loops to improve model accuracy.
Integrated with existing claims management system via APIs to populate data automatically.
Results & Impact
95% of documents now processed automatically without human intervention
Document processing time reduced from 30 minutes to 2 minutes average
Data extraction accuracy: 97.5%
Claims processing cycle time reduced by 60%
Data entry staff reallocated to complex case review and customer service
ROI achieved within 4 months of deployment
Technology Stack
"This system transformed our operations. We process claims faster, more accurately, and our team can focus on helping customers instead of data entry."
Robert Kim
VP of Claims Operations