In today's social media landscape, users express interests through a mix of images and text. This presents an advanced challenge for recommendation systems that need to leverage both deep semantic parsing and AI-driven image recognition to generate relevant suggestions. The system described in this article utilizes a cross-modal, multilayered architecture to integrate textual and visual data through advanced vector retrieval and contextual reasoning. Designed to operate under high-concurrency conditions, this system dynamically responds to complex user needs, showcasing AI's potential for sophisticated social media applications.