AI-POWERED LEGAL ASSISTANT- USING RETRIEVAL AUGMENTED GENERATION (RAG) FOR THE INDIAN JUDICIARY – “NYAYA GYAN”

The Indian judicial system produces vast quantities of legal information every year, including case judgments, statutory updates, and procedural directives.While these resources are essential for justice delivery, accessing and understanding them remains a major challenge for civilians, advocates, and even judges who deal with extensive workloads.This study presents Nyaya Gyan, an AI-powered legal assistant based on the Retrieval-Augmented Generation (RAG) architecture, designed to simplify, accelerate, and improve the legal information retrieval process.By combining vector-based similarity search, language model reasoning, knowledge graph visualization, and role-specific interfaces, the system ensures accurate, context-aware, and citation-backed legal responses.The methodology includes data preprocessing, chunking, embedding generation, FAISS indexing, secure cloud storage via Supabase, and backend implementation using FastAPI.The expanded report covers system architecture, modeling, and performance evaluation in depth.Results indicate reduced manual research time, improved understanding of legal content, easy access to precedents of case, easy drafting process and efficient retrieval for various legal domains.The study concludes that RAG-based legal assistants can significantly enhance digital judicial processes, making legal knowledge more accessible for civilians, while supporting advocates and judges in informed decision-making.