Legal Aid Provider Portal using RAG and AI

Access to legal information remains a major challenge in India due to the complexity of legal language, lack of awareness among citizens, and the high cost associated with professional legal consultation. Many individuals are unable to understand their legal rights and procedures, which often leads to exploitation or misuse of authority. With the rapid advancement of Artificial Intelligence (AI), especially in Natural Language Processing (NLP), it has become possible to design intelligent systems capable of providing real-time assistance in various domains, including law. This paper presents the design and implementation of an AI-based system named Legal Aid Provider Portal, which aims to provide accurate, accessible, and structured legal guidance to users. The system is built using Indian legal documents such as the Constitution of India, Bharatiya Nyaya Sanhita (BNS), and Bharatiya Nagarik Suraksha Sanhita (BNSS). It integrates Retrieval Augmented Generation (RAG) with Large Language Models (LLMs) to ensure that responses are grounded in real legal data and not generated based on general knowledge alone. The proposed system architecture focuses on scalability, efficiency, and low latency, enabling users to receive responses within 1–3 seconds. The system also ensures improved accuracy by retrieving relevant legal sections before generating responses. Experimental observations demonstrate that the system performs better than traditional rule-based and generic AI chatbots in terms of accuracy, reliability, and contextual understanding. This work contributes towards improving legal awareness and making legal assistance more accessible to the general public.

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Publication Details

Journal
Iconic Research and Engineering Journals
Published
2026-04-16
DOI
https://doi.org/10.64388/irev9i10-1716222
Primary Topic
Artificial Intelligence in Law
Type
article
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article

Legal Aid Provider Portal using RAG and AI

Vahid, Suraj T H, Vinod M, Sopnil Patil et al.
Iconic Research and Engineering Journals
Artificial Intelligence in Law
article

Legal Aid Provider Portal using RAG and AI

Vahid, Suraj T H, Vinod M, Sopnil Patil, Aparna
article en

Abstract

Access to legal information remains a major challenge in India due to the complexity of legal language, lack of awareness among citizens, and the high cost associated with professional legal consultation. Many individuals are unable to understand their legal rights and procedures, which often leads to exploitation or misuse of authority. With the rapid advancement of Artificial Intelligence (AI), especially in Natural Language Processing (NLP), it has become possible to design intelligent systems capable of providing real-time assistance in various domains, including law. This paper presents the design and implementation of an AI-based system named Legal Aid Provider Portal, which aims to provide accurate, accessible, and structured legal guidance to users. The system is built using Indian legal documents such as the Constitution of India, Bharatiya Nyaya Sanhita (BNS), and Bharatiya Nagarik Suraksha Sanhita (BNSS). It integrates Retrieval Augmented Generation (RAG) with Large Language Models (LLMs) to ensure that responses are grounded in real legal data and not generated based on general knowledge alone. The proposed system architecture focuses on scalability, efficiency, and low latency, enabling users to receive responses within 1–3 seconds. The system also ensures improved accuracy by retrieving relevant legal sections before generating responses. Experimental observations demonstrate that the system performs better than traditional rule-based and generic AI chatbots in terms of accuracy, reliability, and contextual understanding. This work contributes towards improving legal awareness and making legal assistance more accessible to the general public.

Iconic Research and Engineering JournalsVol. 9(10)
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Artificial Intelligence in Law
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Legal Aid Provider Portal using RAG and AI — Vahid, Suraj T H, et al. · Iconic Research and Engineering Journals (2026) | TGRS Research Map | TGRS