MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202641099810 A) filed by Dr. Nagarajan G; Ms. Geetha N; Ms. Keethi K. S; Dr. S. Thirumal; Dr. Geetha. K; and M. Revathi on August 18, 2026, for Ai-Driven Adaptive Enterprise Decision Support System For Real-Time Predictive And Context-Aware Decision Making.
Inventors include Dr. Nagarajan G; Ms. Geetha N; Ms. Keethi K. S; Dr. S. Thirumal; Dr. Geetha. K; and M. Revathi.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: The present invention discloses an AI-driven adaptive enterprise decision support system for real-time predictive and context-aware decision making. The system receives heterogeneous enterprise data from enterprise applications, databases, operational systems, sensors and external information sources, processes the data for quality and consistency, and generates a dynamic enterprise context state. A predictive intelligence engine generates future-state predictions with confidence and uncertainty information, while a decision optimization engine evaluates candidate actions according to enterprise objectives, operational constraints and risk conditions. An explainable recommendation module generates actionable recommendations together with influencing factors, expected consequences and confidence information. A decision execution and outcome monitoring mechanism observes actual results following implementation of a recommendation. An adaptive learning module compares predicted and observed outcomes, processes authorized user feedback and selectively updates predictive models or decision policies according to detected deviations and changing enterprise conditions. A model governance mechanism monitors model drift and performance degradation and selectively initiates recalibration or retraining. The system thereby establishes a closed-loop architecture comprising data acquisition, contextual intelligence, prediction, optimization, recommendation, execution, outcome monitoring and adaptive learning, enabling continuously improving enterprise decision support across cloud, on-premise and hybrid computing environments. Accompanied Drawing [FIGS. 1-2]
Disclaimer: Curated by HT Syndication.
