The AI-Powered Recommender System for E-commerce enhances user experience by providing personalized product recommendations using advanced machine learning techniques, including collaborative filtering, content-based filtering, and hybrid models. It comprises key modules such as a User Profiling Module for capturing preferences, a Recommendation Engine for generating tailored suggestions, a Real-time Personalization Module that adapts recommendations dynamically, and an A/B Testing Module for optimizing performance. By analyzing browsing history, user preferences, and demographic data, the system intelligently predicts customer needs, boosting satisfaction and sales conversion rates. Seamlessly integrating with e-commerce platforms, it delivers real-time, evolving recommendations, making it an essential tool for maximizing engagement and revenue.