AI-Based Legal Assistant for Indian Legal Awareness | Zenodo Skip to main Communities My dashboard Log in Sign up RS PUBLICATION Published April 17, 2026 | Version v1 Journal article Open AI-Based Legal Assistant for Indian Legal Awareness Authors/Creators Tushar Magar, Dnyaneshwar Lahane, Aditya Bhatkar, Kalpesh Ingle, Atharva Chaudhari and Dr. R. R. Bhure (Research group) 1 Show affiliations 1.
Department of Artificial Intelligence and Data Science, P. R. Pote Patil College of Engineering and Management, Amravati, Amravati, Maharashtra, India Description Highlights • Proposed an AI-powered legal assistant tailored specifically for Indian law to simplify access to legal information for common users. • Developed a Retrieval-Augmented Generation (RAG) based system integrating vector search (Pinecone) with large language models for accurate legal query resolution. • Implemented document analysis capability to extract and summarize key insights from legal documents. • Enabled multimodal interaction through text and voice using speech recognition and text-to-speech technologies. Abstract The increasing complexity of the Indian legal system often makes it difficult for common individuals to access accurate and timely legal information. To address this challenge, this paper presents an AI-based legal assistant designed to improve legal awareness and simplify access to legal information for users in India . The system leverages Large Language Models (LLMs) combined with Retrieval-Augmented Generation (RAG) to deliver context-aware and reliable responses to user queries. The proposed system integrates a vector database (Pinecone) to store and retrieve relevant legal information efficiently, ensuring that responses are not only accurate but also grounded in contextual data. The backend is developed using Flask , while the frontend utilizes React and Tailwind CSS to create a responsive and user-friendly interface. The system also supports document analysis , allowing users to upload legal documents and receive concise summaries and insights. To enhance accessibility, the system incorporates voice-based interaction through speech recognition and text-to-speech technologies, along with multi-language support to cater to diverse users. The proposed system demonstrates improved relevance and usability compared to traditional keyword-based legal search methods. Overall, the system aims to reduce the gap between complex legal knowledge and everyday users by providing an accessible and intelligent support platform. Keywords: AI Legal Assistant, Legal Awareness, Indian Law, NLP, Retrieval-Augmented Generation, Legal Chatbot Files 9.pdf Files (280.7 kB) Name Size Download all 9.pdf md5:ee6f0ab8c7046837ffc84379009c87e6 280.7 kB Preview Download 44 Views 16 Downloads Show more details All versions This version Views Total views 44 44 Downloads Total downloads 16 16 Data volume Total data volume 6.5 MB 6.5 MB More info on how stats are collected.... Versions External resources Indexed in OpenAIRE Communities Keywords and subjects Keywords AI Legal Assistant, Legal Awareness, Indian Law, NLP, Retrieval-Augmented Generation, Legal Chatbot Details DOI DOI Badge DOI 10.5281/zenodo.19632113 Markdown [](https://doi.org/10.5281/zenodo.19632113) reStructuredText .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.19632113.svg :target: https://doi.org/10.5281/zenodo.19632113 HTML <a href="https://doi.org/10.5281/zenodo.19632113"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.19632113.svg" alt="DOI"></a> Image URL https://zenodo.org/badge/DOI/10.5281/zenodo.19632113.svg Target URL https://doi.org/10.5281/zenodo.19632113 Resource type Journal article Publisher RS Publication Published in International Journal of Computer Application, 16(2), ISSN: 2250-1797, 2026. Rights License Creative Commons Attribution 4.0 International The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited. Read more Copyright RS Publication Citation Export Technical metadata Created April 19, 2026 Modified April 19, 2026 Jump up About About Policies Infrastructure Principles Projects Roadmap Contact Blog Blog Support Help FAQ Developers REST API OAI-PMH Contribute GitHub Donate Funded by Powered by CERN Data Centre & InvenioRDM Status Privacy policy Cookie policy Terms of Use This site uses cookies. Find out more on how we use cookies Accept all cookies Accept only essential cookies