Mr. Chinmay Kumar Pradhan, Mr. Muktiranjan Patra, Prof. Smruti Smaraki Sarangi 03 06 The rapid growth of online shopping platforms and digital marketplaces has significantly increased the need for intelligent recommendation systems capable of improving user experience and customer satisfaction Traditional ecommerce platforms often struggle to provide personalized product recommendations based on user interests browsing behavior and purchase history This paper presents the design and implementation of ONEKART an AIbased ECommerce Recommendation Platform developed to provide personalized product suggestions using user preferences and hybrid recommendation techniques The proposed system integrates contentbased filtering collaborative filtering and intelligent recommendation mechanisms to improve product discovery and customer engagement The platform is designed using modern web technologies including Reactjs Tailwind CSS Nodejs Expressjs MongoDB and RESTful APIs to ensure scalability responsiveness and secure communication ONEKART provides features such as user authentication product management shopping cart functionality order tracking AIbased recommendations secure payment integration and admin management The implementation demonstrates improved recommendation accuracy better user engagement and enhanced shopping experiences compared to traditional static ecommerce systems The proposed platform provides a scalable foundation for future intelligent ecommerce applications Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026