MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641107126 A) filed by Madhankumar C; Dr. P. Sowjanya - Andhra Christian College Of Law; Dr. K. Surya Prabha - Andhra Christian College Of Law; Dr. S. V. Sudha - Rathinam Technical Campus; Ms Harini S V - Dr. M. G. R. University; Ms Pooja Tadakal - Sharnbasva University; and Ms P. Vimala Rani - Aaa College Of Engineering And Technology on September 06, 2026, for An Explainable Artificial Intelligence Framework For Real-Time Legal Governance, Public Policy Compliance, And Judicial Decision Support Using Knowledge Graph Analytics.
Inventors include Dr. P. Sowjanya - Andhra Christian College Of Law; Dr. K. Surya Prabha - Andhra Christian College Of Law; Dr. S. V. Sudha - Rathinam Technical Campus; Ms Harini S V - Dr. M. G. R. University; Ms Pooja Tadakal - Sharnbasva University; and Ms P. Vimala Rani - Aaa College Of Engineering And Technology.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: An Explainable Artificial Intelligence Framework for Real-Time Legal Governance, Public Policy Compliance, and Judicial Decision Support Using Knowledge Graph Analytics ABSTRACT An Explainable Artificial Intelligence Framework for Real-Time Legal Governance, Public Policy Compliance, and Judicial Decision Support Using Knowledge Graph Analytics presents an intelligent decision-support framework designed to improve legal governance, regulatory compliance, public-policy evaluation, and judicial decision assistance through Explainable Artificial Intelligence (XAI) integrated with Knowledge Graph Analytics. Modern legal and governance systems involve complex interactions among statutes, constitutional provisions, regulations, judicial precedents, administrative rules, policy documents, and institutional procedures, making manual interpretation and compliance assessment time-consuming and susceptible to inconsistencies. The proposed framework combines knowledge graph construction, semantic legal reasoning, explainable machine learning, real-time policy monitoring, and evidence-linked decision support to provide transparent, interpretable, and legally traceable recommendations while preserving human oversight. The proposed system comprises a legal-document acquisition module, multilingual legal language processing module, knowledge graph construction engine, semantic entity and relationship extraction module, legal reasoning engine, explainable AI module, compliance assessment module, judicial decision-support module, policy-impact analysis module, real time monitoring module, and governance dashboard. Legal information from constitutions, statutes, regulations, judicial decisions, government notifications, administrative orders, public-policy documents, and institutional rules is transformed into an interconnected knowledge graph representing legal entities, obligations, rights, precedents, exceptions, jurisdictions, and procedural relationships. The reasoning engine evaluates relationships among legal provisions, precedents, policy requirements, and contextual facts to identify applicable legal rules and potential compliance obligations. The Explainable AI module generates transparent decision explanations by presenting relevant statutory provisions, precedent relationships, knowledge-graph paths, confidence indicators, legal reasoning chains, and supporting evidence associated with each recommendation. The compliance module continuously evaluates organizational activities against evolving legal and regulatory requirements, while the policy-analysis module identifies potential implementation conflicts, regulatory overlaps, legal inconsistencies, and policy dependencies. Real-time monitoring mechanisms incorporate newly issued legislation, judicial decisions, regulatory amendments, and government notifications to maintain updated legal intelligence. The proposed invention is applicable to judicial decision-support systems, government governance platforms, regulatory compliance management, legal research, public administration, corporate governance, policy evaluation, legislative analysis, and digital justice ecosystems. By combining explainable artificial intelligence with knowledge graph analytics, the framework provides transparent, interpretable, evidence-linked, and context-aware legal intelligence that supports informed decision-making while maintaining accountability, traceability, and human oversight in legal and governance environments.
Disclaimer: Curated by HT Syndication.
