MUMBAI, India, Jan. 7 -- Intellectual Property India has published a patent application (202511103927 A) filed by Prof. Lavkush Sharma; Mr. Rahul Pathak; Mr. Vipul Sharma; Dr. Santosh Bansirao Gaikwad; Dr. N. Srinivasan; Dr. Parmod Kumar; Mrs. Reeta Mishra; and Dr. Shilpa K P, Noida, Uttar Pradesh, on Oct. 28, 2025, for 'a device with a method for ai-driven dynamic pricing system for e-commerce platforms using predictive analytics.'
Inventor(s) include Prof. Lavkush Sharma; Mr. Rahul Pathak; Mr. Vipul Sharma; Dr. Santosh Bansirao Gaikwad; Dr. N. Srinivasan; Dr. Parmod Kumar; Mrs. Reeta Mishra; and Dr. Shilpa K P.
The application for the patent was published on Dec. 12, under issue no. 50/2025.
According to the abstract released by the Intellectual Property India: "The present invention discloses a system, method, and device for implementing an AI-driven dynamic pricing strategy for e-commerce platforms. The invention addresses the limitations of static pricing by providing a real-time, automated, and intelligent pricing solution. The core of the invention lies in the synergistic operation of three primary components: a data aggregation module, a predictive analytics engine, and a dynamic pricing engine. The data aggregation module functions as the sensory input of the system, responsible for the continuous and systematic collection of multi-faceted data. This includes internal data from the e-commerce platform's own database, such as historical sales transactions, current inventory levels, product attributes, and real-time user browsing behavior. Externally, the module gathers data from competitor websites through web scraping techniques to monitor rival pricing strategies and promotional activities. Furthermore, it can ingest broader market intelligence data, including economic indicators and social media trends, to form a comprehensive data landscape. This aggregated raw data is fed into the predictive analytics engine, which serves as the cognitive core of the invention. This engine is implemented using one or more machine learning models, such as regression algorithms, time-series forecasting models, or deep neural networks. The engine is trained on historical data to identify complex, non-linear patterns and correlations. Its primary functions include forecasting future product demand under various hypothetical pricing scenarios, determining the price elasticity of demand for specific products or categories, and identifying temporal windows of opportunity for price adjustments. This engine is self-learning, meaning its predictive accuracy continuously improves as it processes new data over time. The dynamic pricing engine acts as the decision-making and execution unit. It takes the predictive outputs from the analytics engine-such as an expected demand curve-and computes a new, optimal price. This calculation is not performed in a vacuum; it is constrained by a set of configurable business rules defined by the e-commerce platform administrator. These rules can mandate a minimum profit margin, a cap on the rate of price changes to maintain customer trust, or strategic goals like market share capture. The engine then automatically communicates the validated optimal price to the e-commerce platform's product listing management system via Application Programming Interfaces (APIs), ensuring the new price is reflected on the live website without manual intervention. In practice, the invention creates a closed-loop control system for pricing. For instance, if the system detects a competitor has run out of stock for a popular product, the predictive engine might forecast an increase in demand on the host platform, and the pricing engine could responsively calculate a slight price increase to maximize revenue. Conversely, for slow-moving inventory, the system might recommend a strategic discount to stimulate sales and free up warehouse space, all while ensuring the price stays above a predefined minimum margin. The disclosed device embodies this invention in a tangible computing apparatus, comprising a processor, memory, and network interfaces, configured to execute the software instructions that instantiate the described modules and engines. The resulting invention provides a significant technological advancement over prior art, enabling e-commerce businesses to operate with greater efficiency, responsiveness, and profitability in a highly competitive digital marketplace."
Disclaimer: Curated by HT Syndication.
