Conversational AI Personalized Shopping: An Intelligent Chatbot With Multi-Layered Recommendation in E-Commerce

Artificial intelligence and full-stack web technology are combined in the solution to the most distressing issues in online retail. Comfy is the name of this solution. By employing one of the most innovative hybrid recommender systems utilizing conversational AI chatbots and combining it with intent analytics, purchase history, and content-based filtering, it assists customers in making purchasing decisions. Since the Comfy platform is built on the MERN (MongoDB, Express.js, React, Node.js) technology stack, it has two components: An AI-based product recommendation system, and an shopping portal for customers, and a admin analytics console for real-time system analytics. This demonstrates how even small and medium-sized enterprises (SME) can harness the power of advanced AI for hyper-personalization at a highly reasonable cost using open-source technology and a thoughtfully architected API. Other noteworthy attributes include the AI-based progressive payment solution with backend security from Razorpay, unique approaches to the safety and security of e-commerce AI systems, and an adaptive recommendation system with multi-layered filtering and responsiveness. With the test system to reality computing, Comfy shows the possibilities of AI and helps e-commerce systems to incorporate AI, making it an essential tool for companies wanting to create an e-commerce system with AI.

Artificial Intelligence, E-commerce Chatbots, Personalized Recommendations, MERN Stack, Hybrid Filtering, Secure Integration.

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