| Issue |
ITM Web Conf.
Volume 81, 2026
International Conference on Emerging Technologies for Multidisciplinary Innovation and Sustainability (ETMIS 2025)
|
|
|---|---|---|
| Article Number | 01003 | |
| Number of page(s) | 14 | |
| DOI | https://doi.org/10.1051/itmconf/20268101003 | |
| Published online | 23 January 2026 | |
Nyay-Sahayak - integrating legal processes with Al and local languages
1 Assistant Professor, P. R. Pote Patil College of Engineering and Management, Department of Computer Science and Engineering, Amravati, Maharashtra, India
2 P. R. Pote Patil College of Engineering and Management, Department of Computer Science and Engineering, Amravati, Maharashtra, India
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With 47 million pending cases and only 21 judges per million population, India is facing a serious crisis of legal access, which is disproportionately affecting the rural population. This Paper proposes an AI- powered multilingual legal aid platform called Nyay Sahayata, which generates court-compliant documents (FIRs, RTIs, affidavits) in over 22 Indian languages. Our system uses a novel Retrieval Augmented Generation (RAG) framework along with IndicBERT and AI4India's IndicTrans2 for accurate multilingual legal processing. The estimated performance analysis on the proposed framework indicates a document acceptance efficiency of 95.2% from legal authorities, reduced filing time from 15 days to an average of 12.7 minutes, and demonstrated 92.8% accuracy in multilingual legal vocabulary processing. Voice input functionality is designed to help users with low literacy independently prepare legally valid documents. Our findings suggest that AI-powered multilingual legal assistance could significantly improve access to justice for disadvantaged populations. The RAG framework ensures legal accuracy while removing barriers to voice input literacy. This paper proposes a comprehensive framework for voice-enabled multilingual legal AI tailored to developing regions, with the potential to improve global access to justice.
Key words: Access to Justice / Rural Development / Artificial Intelligence / Document Automation / Multilingual Natural Language Processing / Retrieval-Augmented Generation / IndicBERT
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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