Advancements in recommendation systems are focusing on enhancing context-awareness and semantic understanding. A multi-pipeline approach combining large language models (LLMs) and traditional algorithms is being implemented to improve personalization. This hybrid system leverages deep learning for natural language understanding while optimizing structured data processing. The goal is to enhance recommendation accuracy, user engagement, and adaptability across various domains.