AI/ML Infrastructure

AI-Powered Document Processing Platform

Automating federal document processing with AI-powered extraction, classification, and intelligent routing at enterprise scale.

95%

Extraction Accuracy

10,000+

Documents per Month

12-Week

Production Delivery

Sector:Federal Civilian

Client:Federal Civilian Agency

Duration:7 months

Role:AI/ML Platform Architecture & Delivery

Overview

EaseOrigin designed and deployed an AI-powered document processing platform for a federal agency handling thousands of forms, applications, and correspondence monthly. The platform combines optical character recognition, large language model orchestration, and custom extraction pipelines to automate document intake, data extraction, classification, and routing, reducing manual processing time and improving accuracy.

The Challenge

The agency processed over 10,000 documents monthly through manual review, with staff spending significant time on data entry, classification, and routing. Error rates from manual processing caused downstream delays, and peak submission periods created backlogs. The agency needed to maintain accuracy while dramatically reducing processing time and manual labor.

Our Solution

EaseOrigin built a multi-stage processing pipeline using AWS Textract for OCR, AWS Bedrock for LLM-powered extraction and classification, and custom LangChain agents for intelligent routing and validation. The platform includes a human-in-the-loop review interface for low-confidence extractions, automated quality scoring, and comprehensive audit trails for compliance. A React-based dashboard provides real-time processing metrics and queue management.

Results

Automated processing of 10,000+ documents per month

Extraction accuracy exceeding 95% across all document types

Processing time reduced by 80% compared to manual review

Human-in-the-loop interface for quality assurance on edge cases

Complete audit trail for all processed documents

Real-time dashboard for processing metrics and queue management

Technologies Used

AWS BedrockAWS TextractLangChainPythonFastAPIPostgreSQLReactS3

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