Intellectual Property India Publishes Patent Application for A System And Method For Ai-Driven Political Strategy Optimization And Governance Performance Assessment

MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202621071273 A) filed by Dr. Sudhakar Shyamrao Shrirame; Dr. Vaishali Sheshrao Perke; and Satyashil Yuvraj Kolekar on June 08, 2026, for A System And Method For Ai-Driven Political Strategy Optimization And Governance Performance Assessment.

Inventors include Dr. Sudhakar Shyamrao Shrirame; Dr. Vaishali Sheshrao Perke; and Satyashil Yuvraj Kolekar.

The application for the patent was published on July 31, 2026, under issue no. 31/2026.

Abstract: ABSTRACT A System and Method for AI-Driven Political Strategy Optimization and Governance Performance Assessment The present disclosure relates to a system and method for AI-driven political strategy optimization, governance performance assessment and adaptive policy impact intelligence The system includes a processor, memory, communication interface, Governance Digital Twin Generation Module, Federated Civic Intelligence Learning Module, Multi-Source Data Authenticity Validation Module, Policy Impact Simulation Engine, Governance Knowledge Graph Engine, Dynamic Strategy Optimization Module, Explainable Governance Intelligence Module, and Autonomous Governance Recommendation Module. The system collects governance related data from multiple heterogeneous sources and performs authenticity validation, privacy-preserving federated learning, governance digital twin generation, citizen sentiment fusion analytics, policy impact simulation, governance drift detection, and adaptive resource allocation optimization. The system also builds governance knowledge graphs and creates explainable governance intelligence for transparent decision support. The system generates governance recommendations, performance evaluations, policy predictions, and audit reports on its own, based on the intelligence generated. The invention improves the accuracy of governance prediction, the efficiency of resource utilization, the evaluation of policy effectiveness, the transparency of administration and the intelligent decision-making of governance through a privacy-preserving and adaptive computational framework.

Disclaimer: Curated by HT Syndication.