Introduction
In legal tech, time is money. Law firms, legal ops teams, and compliance departments are flooded with contracts, policies, NDAs, and regulatory documents that need to be read, flagged, summarized, and routed.
Manual summarization is time-consuming, error-prone, and costly. AI promises to accelerate this process but accuracy and legal reliability are non-negotiable. In this use case, we’ll show how DataPro helped a fast-growing legal tech company deploy AI-powered summarization that cut review time by 65% while maintaining precision and control.
The client, a legal workflow automation provider, was scaling fast and needed a reliable summarization engine for:
Their current system used basic keyword matching and regex-based extraction. It missed context, handled nuance poorly, and failed on non-standard clause formats.
DataPro worked with the client’s legal engineers and product managers to build a custom AI pipeline based on Retrieval-Augmented Generation (RAG) and domain-tuned LLMs.
After full rollout across the platform:
The client is now expanding to: