This project showcases a working prototype of a Legal AI Risk Analyzer built using Retrieval-Augmented Generation (RAG), FAISS vector search, and a local Llama3 model. The system ingests contract documents, breaks them into contextual clauses, retrieves semantically similar clauses from a vector database, and uses the LLM to assess risk levels, reasoning, and recommendations. Designed entirely for local deployment, it ensures data privacy while demonstrating how enterprise teams can analyze legal and compliance risks without exposing sensitive content to external APIs.