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The rapid expansion of e-commerce platforms has resulted in a vast variety of product options for consumers, making it difficult to discover the most relevant things that fit their unique requirements. This research article proposes a novel strategy for improving the online shopping experience using generative artificial intelligence (AI) approaches. The proposed approach blends scenario-based product matching with AI-powered product description generation to deliver personalized suggestions and engaging product descriptions based on individual consumer preferences. The system uses natural language processing and fine-tuned language models to analyze user-provided scenarios and determine the most relevant products based on cosine similarity. It then generates interesting product descriptions that highlight essential features and benefits, resulting in an engaging and informative purchasing experience.