The Indian judicial system heavily relies on precedents for legal interpretations and decision making, providing access to relevant case law a critical yet time consuming task for legal professionals and researchers. This paper presents an AI-powered Legal Case Search Engine designed to transform legal research by leveraging advancements in Natural Language Processing (NLP) and Large Language Models (LLMs). The system enables efficient retrieval of contextually relevant legal precedents from the Supreme Court of India’s judgments, utilizing techniques like vector embeddings, cosine similarity, and semantic search. It offers concise case summaries and metadata insights to streamline decision making and improve accessibility to legal data. Built on open-source technology, the platform emphasizes scalability, cost efficiency, and user centric design, ensuring adaptability for future enhancements like multilingual support. By democratizing access to legal knowledge, this research aims to bridge the gap between complex legal texts and their practical application, fostering innovation in legal workflows and enhancing the rule of law.