Clegora – Legal ChatBot for Indian Consumer and Civil Rights

The current paper brings a design, development and evaluation of an AI-based legal assistant named Clegora to suit the requirements of the Indian legal system. However, based on a state-of- the-art large language model, Groq Llama 3.2, deployed in a Retrieval-Augmented Generation (RAG) framework, Clegora delivers contextual and high-quality responses through the dynamic retrieval of relevant legal documents in a specialized vector database. The system uses a new token management approach that scales input lengths based on query complexity with the aim of being efficient in resource utilization without compromising on the quality of responses. Clegora has privacy and ethical standards, as it is built with secure authentication of the user by Firebase and strong content safety measures. Performance tests show short response times of less than five seconds to simultaneous users and citation efficiency of more than 95%. The responses of the users point out how the assistant could be used to simplify complex legal cases, multi-turn conversations, and provide users with confidence when handling legal cases. Though the existing constraints are the processing of language diversity in the region and very narrow domain queries, the modular design and continual data refreshing makes Clegora a scalable solution that will democratize the access to legal information, enabling informed decision-making in diverse Indian populations.