LEGAL AI: An AI-Powered Legal Research and Case Prediction System for the Indian Judiciary

Abstract: This paper presents the design and implementation of LEGAL AI, an artificial intelligence-powered legal research and case prediction system customized for the Indian judicial context. It leverages a fine-tuned LLaMA-2 model and InLegalBERT using transfer learning and domain adaptation to provide functionalities such as case outcome prediction, legal explanation generation, and legal question answering (Legal QA). The system employs a Streamlit interface and FAISS-based vector search to retrieve relevant legal documents and provide contextual legal insights. With domain-specific fine-tuning and quantized models for CPU inference, LEGAL AI enhances accessibility, interpretability, and efficiency in legal research and decision-making.

Keywords: Legal AI, LLaMA-2, InLegalBERT, Legal Question Answering, Indian Judiciary, FAISS, Domain Adaptation , Retrieval-Augmented Generation.