Automating Document Processing with AI for a Legal Tech SaaS

The Challenge

The client's platform helps mid-size law firms manage contracts. Their customers were uploading thousands of contracts daily, but key data extraction was still manual — paralegals spent hours per contract identifying key dates, obligations, termination clauses, and risk factors. The client had experimented with basic NLP but couldn't achieve the accuracy needed for legal documents. They needed a solution that was accurate enough to trust, fast enough to scale, and flexible enough to handle different contract types.

Our Solution

We built a multi-stage AI pipeline over a 14-week engagement. The system uses OCR for scanned documents, an LLM-based extraction layer for identifying and categorizing contract clauses, a custom fine-tuned classifier for risk scoring, and a human-in-the-loop review interface for edge cases. We implemented RAG with a vector database to give the LLM context from the firm's own precedent library. The system processes documents asynchronously, with results available in under 2 minutes per contract. We built comprehensive evaluation pipelines and monitoring to track accuracy over time.

Results

• 75% reduction in contract review time
• 94% accuracy on key term extraction (validated against human reviewers)
• Processing capacity increased from 50 to 500+ contracts per day
• Risk flag accuracy of 91%, catching issues human reviewers occasionally missed
• System handles 15+ contract types across 3 jurisdictions

Technologies Used