MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202621099835 A) filed by Pravin Shegade on August 18, 2026, for Adaptive The Impact Of Agentic Ai On Autonomous Exception Management And Real-Time Decision-Making In Global Supply Chains..
Inventor includes Pravin Shegade.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: ABSTRACT [505] The agentic AI-based supply chain framework introduces an innovative autonomous exception-management architecture for global supply chain networks that integrates real-time decision-making protocols with adaptive disruption-response mechanisms, facilitating continuous shipment monitoring, dynamic resource reallocation, and robust exception resolution while maintaining seamless integration across distributed logistics environments and operational accuracy for consistent enterprise applications. [510] The comprehensive supply chain framework employs adaptive agentic algorithms and intuitive decision-making protocols, utilizing embedded computational reasoning arrays and latency-efficient inference systems to ensure timely exception identification, enhanced operational understanding, and optimal disruption-recovery reliability while maintaining continuous supply chain monitoring capabilities across heterogeneous logistics nodes. [515] The integrated methodology combines multi-agent coordination techniques with artificial intelligence-driven pattern recognition systems, leveraging variable- precision logistics signals and multi-factor disruption indicators to optimize exception-resolution procedures and decision-making workflows for maximum operational accuracy and minimal response-latency uncertainty during critical supply chain applications. [520] The novel responsive agentic architecture features engineered high- precision decision-making components with specialized shipment-fingerprinting protocols, enabling complex multi-stage exception verification while ensuring monitoring consistency and performance optimization across various supply chain instruments and logistics networks without compromising system reliability. [525] The innovative design incorporates strategic validation mechanisms for enhanced exception identification and operational security, utilizing optimized multi-function agentic systems and adaptive decision-making technology to ensure legitimate corrective action while maintaining functionality across diverse global trade environments and disruption scenarios. [530] Implementation methodology emphasizes scalable supply chain integration and efficient resolution sequences, implementing interactive monitoring measures and pattern recognition algorithms to achieve superior disruption determination, enhanced exception identification, and unauthorized-intervention prevention while ensuring technological simplicity during continuous operational oversight. [535] The system demonstrates exceptional adaptability through comprehensive integration of exception-management protocols and intelligent decision-making technologies, validating its effectiveness across various multi-tier supply chain configurations and global trade scenarios while maintaining consistent monitoring performance and operational efficiency under diverse conditions. [540] The developed framework enables sustainable and resilient operation of global supply chains through streamlined, agentic AI-powered decision systems, providing significant advantages over traditional exception-handling approaches through variable validation mechanisms, adaptive resolution protocols, and improved real-time decision-making while maintaining superior response accuracy during critical logistics procedures.
Disclaimer: Curated by HT Syndication.
