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AI-Native Product LegalTech
Legal Tech RAG Engine
Vector-based retrieval for processing 50k+ legal documents.
The Outcome
Document review time cut by 60%. Search accuracy improved by factor of 10x over keyword search.
Tech Stack
Next.js OpenAI Pinecone LangChain Vercel
Technical Bottlenecks
Lawyers spent 40% of their time manually Ctrl+F searching through thousands of PDF contracts. Keyword search failed to capture semantic meaning (e.g., 'termination' vs 'end of contract').
The Solution Design
High-level System Design
We built a RAG (Retrieval-Augmented Generation) pipeline. Documents are chunked, embedded via OpenAI, and stored in Pinecone. A Next.js frontend allows natural language querying.
Engineering Rigor
- Implemented automated CI/CD pipelines ensuring 99.9% uptime.
- Comprehensive unit and integration testing coverage using standard libraries.
- Full documentation of API endpoints and system dependencies.