MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202641043377 A) filed by Dr. M. Swapna; Dr. T. Raghunadha Reddy; K Narsimhulu; T. Harikrishna; V. Sowjanya; and Mr. Bikshapathy Peruka, Hyderabad, Telangana, on April 5, for 'adaptive ai-based decision intelligence system for business optimization.'
Inventor(s) include Dr. M. Swapna; Dr. T. Raghunadha Reddy; K Narsimhulu; T. Harikrishna; V. Sowjanya; and Mr. Bikshapathy Peruka.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "An adaptive artificial intelligence (AI)-based decision intelligence system for optimizing business operations is disclosed, wherein the system integrates heterogeneous data from multiple internal and external sources, including enterprise systems, transactional databases, and real-time data streams, to enable unified and comprehensive analysis. A data processing module transforms raw data into structured features, which are utilized by a hybrid AI decision engine incorporating supervised learning, unsupervised learning, and reinforcement learning techniques to generate predictions, discover patterns, and dynamically optimize decision strategies. The system further includes a contextual intelligence module configured to apply domain-specific rules, constraints, and environmental variables to ensure that generated decisions are relevant, feasible, and aligned with organizational objectives. A decision execution layer enables automated implementation or user-assisted execution through dashboards, interfaces, and application programming interfaces. Additionally, an adaptive learning module establishes a closed-loop feedback mechanism, wherein outcomes of executed decisions are continuously monitored and used to retrain and refine the underlying models, thereby improving accuracy and performance over time. By enabling real-time, context-aware, and self-improving decision-making, the invention enhances operational efficiency, reduces manual intervention, and improves overall business performance across diverse domains, while remaining scalable and adaptable to various industry applications."
Disclaimer: Curated by HT Syndication.
