Scaling AI in Legal: Building Uber's Redlining Agent

Uber describes building its first-generation Legal Redlining Agent (LRA), a Microsoft Word add-in that reviews counterparty redlines, detects intent, recommends policy-aligned responses, generates comments, and flags risks for lawyer review. Through four iterations—RAG, lawyer feedback loops, tone modulation, and agentic modifications plus a rules database—Uber reports over 20% reduction in average contract review time and 91% accuracy in AI-generated decisions. The post details the architecture (React/TypeScript add-in, Python back end, LangGraph workflow, OpenSearch vector stores, Redis session memory) and time-weighted feedback sampling to mitigate concept drift.