AI-Based E-Commerce Website Using MERN Stack

Abstract

The rapid growth of digital commerce platforms has transformed the global retail industry by enabling users to purchase products online with greater convenience, speed, and accessibility. Traditional shopping systems often suffer from limitations such as restricted operating hours, lack of personalized recommendations, manual inventory handling, and inefficient order tracking processes. Modern e-commerce platforms aim to overcome these limitations by integrating intelligent automation, secure online transactions, and responsive web technologies. This research presents the design and development of an AI-Based E-Commerce Website using the MERN stack (MongoDB, Express.js, React.js, and Node.js). The proposed platform provides secure user authentication, dynamic product browsing, advanced product search and filtering, shopping cart management, real-time order tracking, and secure payment gateway integration using Razorpay and Stripe APIs. The system also supports responsive cross-device accessibility and centralized administrative management for products, inventory, users, and transactions. The platform follows a scalable three-tier MVC architecture and utilizes MongoDB with Mongoose ODM for structured schema validation and optimized query handling. Cloud-based image storage is integrated to reduce server load and improve media delivery performance. Furthermore, the system includes a foundation for AI-driven recommendation systems and future intelligent analytics modules. Experimental evaluation demonstrates that the proposed system improves shopping efficiency, transaction reliability, and user experience while maintaining scalability and security for high-traffic e-commerce environments.