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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM48096

Legal Solutions - GenAI

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM48096

Volume:

9 |

5 |

May 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM48096

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PDN

Prof. Deepak Nair

RZ

Raiyan Zoha

SSH

Sahib Singh Hans

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Abstract

This paper presents LegalRAG Assistant, an AI-powered legal chatbot platform that leverages Generative AI (GenAI), Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) to provide accurate, context-aware responses to legal queries. The system integrates Indian legal frameworks including the Bharatiya Nyaya Sanhita (BNS) and RERA guidelines to support real-time legal consultation and document analysis. A structured pipeline was developed using vector embeddings (via Sentence-BERT) and FAISS for efficient semantic retrieval of legal texts, which are then fed into a fine-tuned LLM (Mistral-7B-Instruct) for answer generation. The platform demonstrates over 90% retrieval precision on a curated legal dataset and supports multilingual, user-friendly interaction through a Gradio-based chatbot interface. Experimental outcomes emphasize LegalRAG Assistant’s readiness for deployment in legal advisory applications, especially in domains requiring rapid access to complex legal information with high accuracy and explainability.

KEYWORDS

LegalTech · Real Estate Law · Property Law · Generative AI · Legal Chatbot · RERA Compliance · Stamp Duty · Legal Document Simplification · Personalized Legal Assistance · Multilingual Support · Access To Justice · RAG

Cite This Article

Prof. Deepak Nair, Raiyan Zoha, Sahib Singh Hans, "Legal Solutions - GenAI," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 5, May 2025. https://doi.org/10.55041/IJSREM48096

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Publication Date

5/17/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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0

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2

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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