AI-Powered Document Processing
Replacing manual invoice processing with a validated AI extraction pipeline
Reduced manual processing by 87%
Improved extraction accuracy to 96%
Cut processing time from hours to minutes
Overview
Document processing automation is one of those use cases where the ROI is obvious — but the path from idea to reliable production system requires careful research and validation before investing in full development. We designed, prototyped, and validated an AI pipeline for document classification and data extraction, giving the client the evidence and architecture needed to commit to full-scale implementation with confidence.
The Challenge
A business processed thousands of invoices and contracts manually, resulting in delays, data entry errors, and a team spending significant time on work that could be automated.
The Solution
Researched, prototyped, and validated an AI pipeline for document classification, OCR extraction, data structuring, and validation — delivered as a production-ready proof of concept.
How We Approached It
Feasibility Research
Evaluated OCR engines, document classification approaches, and LLM-based extraction methods across a sample of real client documents.
Pipeline Design
Designed a modular pipeline: classify → extract → structure → validate → route exceptions — with confidence thresholds at each stage.
Prototype Development
Built and tested a working prototype on a representative document sample, measuring accuracy against manually verified ground truth.
Integration Specification
Delivered the validated pipeline with full integration documentation so the development team could implement production deployment.
Key Features Built
Results & Impact
Reduced manual processing by 87%
Improved extraction accuracy to 96%
Cut processing time from hours to minutes
Technologies
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