From 15 minutes to 45 seconds per document
A legal tech company processed over 2,000 contracts daily. Each document required manual review — classification by type, extraction of key clauses, dates, and party names, then entry into their database. This took an average of 15 minutes per document, creating a bottleneck that cost roughly $40,000/month in labor alone.
I designed an end-to-end pipeline with four stages. PDF ingestion with OCR, GPT-4 classification with confidence scoring, structured data extraction into a normalized schema, and PostgreSQL storage with full audit trails. A review dashboard handles only the 6% low-confidence extractions.
FastAPI for async orchestration, Tesseract + commercial OCR fallback, 14 prompt iterations for production accuracy, and a cost control layer routing simple docs to GPT-3.5-turbo — cutting API costs by 60%.
Processing time dropped from 15 minutes to 45 seconds. 94% first-pass accuracy. $35,000/month saved. 180,000+ documents processed with 99.8% uptime.
Let's discuss your project — I'll tell you what's realistic and how long it'll take.
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