University admissions offices face mounting challenges in providing consistent, personalized guidance to thousands of prospective students while managing limited human counselor resources, creating an urgent need for intelligent digital solutions that maintain high-quality interactions. Current approaches including text-based chatbots and basic virtual assistants fail to establish meaningful emotional connections with users, struggle with complex contextual conversations, and typically operate as isolated tools rather than integrated components of a comprehensive admission ecosystem. We propose the Smart Metahuman Admissions Consulting System that addresses these limitations through three integrated technologies: a Retrieval-Augmented Generation pipeline achieving over 95% query accuracy with only 0.76-s response time, an Ernerf-based metahuman-rendering system creating photorealistic facial animations that maintain strong user visual engagement, and a multimodel edge computing framework that optimizes processing of multilingual interactions with only a 3.5% accuracy decrease for bilingual conversations. Experimental evaluations with our system demonstrated exceptional performance in handling both general admission inquiries (96% accuracy) and complex contextual questions, while creating such a convincing human-like experience that many participants reported moments where they forgot they were interacting with an AI system, confirming our approach provides an immersive consultation experience while offering institutions a scalable solution for modernizing their admission processes.