NyayaSakhi–SWATI: India’s First Statute-Aligned, Retrieval-Augmented LAMP² 4.0 AI-Powered Digital Legal Companion for Victims of Domestic-Violence
DOI:
https://doi.org/10.16920/jeet/2026/v39is2/26071Keywords:
Artificial intelligence; Domestic violence; Retrievalaugmented generation; Statutory relief predictionAbstract
Domestic violence (DV) remains a pervasive challenge in India, and survivors frequently struggle to obtain timely, comprehensible, and statute-accurate information about their rights under the Protection of Women from Domestic Violence Act, 2005 (PWDVA). Existing helplines and portals are typically static, FAQ-based, or rule-driven, offering neither interactive legal literacy nor case-specific guidance grounded in statutory relief structures. This paper presents NyayaSakhi–SWATI, India’s first statute-aligned, retrieval-augmented AI legal companion for DV survivors, powered by the LAMP² 4.0 backend. SWATI (Support and Welfare Assistance through Technology Interface) is designed as an empathetic “AI NyayaSakhi” that securely collects survivor narratives, retrieves PWDVA-aligned precedents from the NyayaSmriti vector knowledge base, and delivers plain-language responses on likely statutory reliefs, indicative case duration, and prescriptive next steps. At the core of the system is the Statute- Aligned Legal Relief Prediction (SALRP) task, wherein LAMP² 4.0 predicts multi-relief outcomes (protection, residence, custody, monetary relief, and compensation) directly from narrative inputs. On the NyayaSmriti evaluation set, LAMP² 4.0 achieves an accuracy of 81%, outperforming strong Indian legal-AI baselines including INLegalLlama, PredEx, and NyayaRAG by margins of approximately +8–9 percentage points and +13.93 percentage points respectively. A single-case reference evaluation against an adjudicated PWDVA matter demonstrates complete alignment between predicted and judicially granted reliefs. A research preview study with domestic-violence survivors and experienced PWDVA practitioners further indicates that NyayaSakhi–SWATI is perceived as usable, empathetic, and statute-faithful. Together, these findings show how retrieval-augmented, statute-aligned AI can move beyond judgment-centric prediction toward survivor centric, pre-adjudicative decision support in domestic-violence litigation.
Downloads
Downloads
Published
How to Cite
Issue
Section
References
Government of India. (2005). The Protection of Women from Domestic Violence Act. Ministry of Law and Justice.
National Judicial Data Grid. (2025). District Court Dashboard. Government of India.
Hasan, K. S. (2025). JusticeNetBD: Context-aware AI to enhance legal information access for Bangladeshi women via retrieval-augmented generation.
Awasekar, D., & Lobo, L. (2024b). Artificial Intelligence for Legal Assistance: A Prescriptive Analytics Model Integrating Social Emotional Learning for Assisting Victims of Domestic Violence in India. In Technology 4 Education Conference. Springer.
Bankata, P., & Mishra, D. T. (2025). Legal protection of women in India: A critical study in the light of recent developments. International Journal of Legal Research.
Shukla, A., Bhattacharya, P., Poddar, S., Mukherjee, R., Ghosh, K., Goyal, P., & Ghosh, S. (2022). Legal case document summarization: Extractive and abstractive methods and their evaluation.
Malik, V., Sanjay, R., Nigam, S. K., Ghosh, K., Guha, S. K., Bhattacharya, A., & Modi, A. (2021, August). ILDC for CJPE: Indian legal documents corpus for court judgment prediction and explanation.
Nigam, S. K., Balaramamahanthi, D. P., Mishra, S., Shallum, N., Ghosh, K., & Bhattacharya, A. (2025, January). NYAYAANUMANA and INLEGALLLAMA: The largest Indian legal judgment prediction dataset and specialized language model for enhanced decision analysis. In Proceedings of the 31st International Conference on Computational Linguistics (pp. 11135-11160).
Nigam, S. K., Patnaik, B. D., Mishra, S., Thomas, A. V., Shallum, N., Ghosh, K., & Bhattacharya, A. (2025). Nyayarag: Realistic legal judgment prediction with rag under the indian common law system.
Awasekar, D. D., & Lobo, L. M. R. J. (2025). Artificial intelligence for legal assistance: A prescriptive analytics model integrating social emotional learning for assisting victims of domestic violence in India. In S. Mishra, A. Kothiyal, S. Iyer, S. Sahasrabudhe, A. Lingnau, & R. Kuo (Eds.), Proceedings of the International Conference on Technology 4 Education 2024, Volume 2. Lecture Notes in Educational Technology. Springer, Singapore.
Nigam, S. K., Sharma, A., Khanna, D., Shallum, N., Ghosh, K., & Bhattacharya, A. (2024). Legal judgment reimagined: PredEx and the rise of intelligent AI interpretation in Indian courts. ACL 2024, 4296– 4315. Association for Computational Linguistics.
Access to login into the old portal (Manuscript Communicator) for Peer Review-

