AI Jurist: empowering legal knowledge and practices in India

In the field of legal studies and other related fields, identifying and to study accurate legal information, such as laws and case precedents, is a difficult challenge. The primary focus of this research is to utilise Natural Language Processing (NLP) and AI techniques for Legal Information Retrieval System to solve this challenge. This system will help lawyers and legal practitioners in building strong arguments, developing effective strategies, and making well-informed decisions critical for successful judicial proceedings. Additionally, it empowers individuals, even without prior legal expertise, to enhance their legal knowledge and better understand the law. Our study used a dataset of 70 thousand records where each record comprises case titles, proceedings, authors, citations, and legal related information. The input options for the system are either legal documents like FIRs or Query containing legal questions in the format of PDFs or Images. Afterwards, utilising the capabilities of LLMs the output is a detailed structured Legal Research Report that consists of prior cases, judgements, laws, courts etc. The system will exponentially boost efficiency by providing precise, time-saving, and easily accessible information with enhanced retrieval accuracy. The evaluation metrics yielded an 80% accuracy in quantitative evaluations, complemented by positive feedback from legal professionals highlighting the system's efficacy in delivering accurate, comprehensive, and relevant legal research reports. These results showcase the potential of proposed solution for practical implementation and further evaluations for its use in the legal domain. The proposed system has the capability to be a companion to humans in information gathering and understanding, thereby contributing towards the improvement of legal knowledge, legal research and the decision-making process.