MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202641110903 A) filed by Sree Chaitanya College Of Engineering on September 16, 2026, for Ai-Driven Predictive Framework For Corporate Working Capital Optimization.
Inventors include Peddi Harini, Assistant Professor, Mba, Sree Chaitanya College Of Engineering; Burra Srinivas Assistant Professor, Mba, Sree Chaitanya College Of Engineering; Chitimalla Padma Assistant Professor, Mba, Sree Chaitanya; and Konde Deepa, Assistant Professor, Mba, Sree Chaitanya.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: The present invention relates to an artificial-intelligence-enabled computer-implemented framework for predictive analysis and optimization of corporate working capital. The framework comprises an enterprise data acquisition module configured to receive heterogeneous operational and financial data from enterprise resource planning systems, accounting systems, sales systems, procurement systems, inventory systems, banking interfaces and other enterprise data sources. A data processing module cleans, normalizes, synchronizes and transforms the received data into machine-processable features. An artificial intelligence prediction engine generates future predictions relating to cash flow, accounts receivable, accounts payable, inventory requirements and liquidity conditions. A dynamic working-capital state generation module generates a continuously updated computational representation of the working-capital condition. A risk assessment module identifies potential liquidity gaps, receivable delays, inventory excesses and payment-related risks. An optimization engine determines an optimized working-capital configuration subject to operational and financial constraints. A scenario simulation module evaluates alternative operating conditions, and a feedback module compares predicted and subsequently observed conditions for continuous model adaptation. The framework thereby provides predictive, adaptive and data-driven optimization of corporate working-capital parameters.
Disclaimer: Curated by HT Syndication.
