You can build a semantic search system for legal documents by combining Pinecone (a vector database), GPT-4 (for intelligent retrieval), and LangChain (to orchestrate the pipeline). This setup lets law firms search case law, contracts, and precedents by meaning rather than keyword matching - so a query like "wrongful termination without cause" surfaces relevant statutes even when documents use different phrasing. The result is a retrieval-augmented generation (RAG) system that feeds the most relevant legal context to GPT-4, so it can cite sources and answer with accuracy.
What you need
The tech stack below represents a realistic, minimal setup to ship a working legal document semantic search system. Prices are current as of August 2024; verify each provider's current terms before committing.
Tool
Plan / Cost
