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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65268
Volume:
10 |
6 |
Jun 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
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.
Computer Engineering
Sinhgad College Of Engineering
Computer Engineering
Sinhgad College Of Engineering
Computer Engineering
Sinhgad College Of Engineering
Computer Engineering
Sinhgad College Of Engineering
Computer Engineering
Sinhgad College Of Engineering
In today’s digital era, the legal sector remains difficult for ordinary people because of complex legal terminology, lack of awareness, and expensive consultation processes. Individuals and small businesses often face challenges in understanding legal contracts, preparing agreements, and validating legal clauses. Traditional legal consultation methods are often time-consuming and costly, making legal assistance inaccessible for many users. This paper presents JurisAI, an AI-powered legal assistance platform developed using Artificial Intelligence (AI), Natural Language Processing (NLP), and Retrieval-Augmented Generation (RAG). The proposed system provides four major functionalities: constitution-based legal advisory, multilingual legal document generation, legal document summarization, and agreement clause verification. The frontend of the system is developed using React.js, while the backend integrates Django, OpenAI APIs, FAISS retrieval, and NLP frameworks. Experimental results demonstrate fast response generation, scalable document processing, and high module accuracy. JurisAI improves accessibility, transparency, and efficiency in legal services for users with limited legal expertise.
KEYWORDS
JurisAI successfully demonstrates how Artificial Intelligence and Natural Language Processing can improve legal ac-cessibility and transparency through intelligent automation. The proposed system integrates legal advisory, multilin-gual document generation, document summarization, and clause verification into a unified platform. Experimental analysis confirmed high accuracy, scalable performance, and efficient response generation. JurisAI represents an important step toward accessible and trustworthy AI-driven legal systems capable of supporting both individuals and or-ganizations.Furthermore, the proposed framework highlights the growing potential of AI-assisted legal ecosystems in reducing legal complexity and improving public engagement with judicial processes. Thus, JurisAI establishes a strong foundation for future intelligent legal platforms that promote faster, more reliable, and user-friendly legal assistance.
[1] LawPal Team, “RAG Legal Chatbot: Constitution-grounded AI Legal Advisor,” arXiv preprint arXiv:2402.01896, 2024. [2] OpenAI, “GPT Models and Retrieval-Augmented Generation Framework,” OpenAI Technical Overview, 2024. [3] Hugging Face, “Transformers and NLP Pipelines,” Hugging Face Documentation, 2024. [4] Django Software Foundation, “Django Framework Documentation,” Version 4.2, 2024. [5] FAISS Team, “Efficient Similarity Search using FAISS,” Meta AI Research, 2024. [6] Legal NLP Researchers, “Proprietary Document Generation using MAW and NyayaShilp Model,” arXiv preprint arXiv:2503.04125, 2025.
Publication Date
6/21/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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