MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541124860 A) filed by Dr. Polasi Sudhakar; Bhanu Prakash Pandiri; Jayanth Vasa; Sai Reddy Mandala; Venkata Krishna Bharadwaj Parasaram; Dr. Srinivasan Nagaraj; Dr. J. Anitha; and Dr. Ch. Asha Immanuel Raju, Eluru, Andhra Pradesh, on Dec. 10, 2025, for 'big data mining method and artificial intelligence system for remote order information.'
Inventor(s) include Dr. Polasi Sudhakar; Bhanu Prakash Pandiri; Jayanth Vasa; Sai Reddy Mandala; Venkata Krishna Bharadwaj Parasaram; Dr. Srinivasan Nagaraj; Dr. J. Anitha; and Dr. Ch. Asha Immanuel Raju.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "The invention provides an integrated big data mining method and artificial intelligence system designed to autonomously collect, process, and analyze remote order information originating from diverse digital platforms. Modern transactional environments generate large volumes of dispersed, multi-format order data from e-commerce systems, mobile applications, logistics networks, and enterprise management platforms. The invention addresses the complexity of this environment by introducing a unified framework capable of transforming heterogeneous and unstructured inputs into structured analytical models suitable for real-time interpretation and predictive evaluation. The system employs automated data acquisition mechanisms that gather structured, semi-structured, and unstructured order information, followed by intelligent cleaning, normalization, and feature extraction processes. Advanced natural language processing and semantic analysis enable the system to interpret contextual order details such as customer messages, product specifications, and logistics notes. Machine learning models-operating across supervised, unsupervised, and reinforcement learning techniques-continuously learn from historical and incoming data to identify patterns, detect anomalies, and generate accurate forecasts related to customer demand, inventory levels, and supply chain performance. A real-time processing engine ensures that insights are produced with minimal latency, allowing organizations to respond quickly to dynamic market conditions. The system also includes automated decision-support functions capable of recommending or executing actions such as inventory adjustments, logistics optimization, and customer notifications. A cross-platform integration module maintains synchronized data flows across multiple digital sources while ensuring scalability, reliability, and data integrity. By combining big data mining, artificial intelligence, real-time analytics, and automated decision-making into a single cohesive solution, the invention significantly enhances operational efficiency, predictive accuracy, and strategic planning in remote order management. It provides organizations with an intelligent and adaptable tool for achieving higher degrees of automation, responsiveness, and data-driven control across distributed commercial ecosystems."
Disclaimer: Curated by HT Syndication.
