Objective: To develop an AI-powered system that accurately detects retinal diseases from OCT retinal images and provides intelligent recommendations for early diagnosis and clinical decision support. Goal: To assist ophthalmologists and patients by enabling fast, reliable, and automated retinal disease detection using deep learning and Generative AI technologies. Research Gap: Conventional retinal disease diagnosis requires expert interpretation, is time-consuming, and lacks integrated AI-based recommendation systems for accessible and efficient decision-making. Result: The developed model successfully classified multiple retinal diseases with high accuracy and generated AI-assisted recommendations, improving diagnostic efficiency and supporting early disease detection. Future Scope: The system can be enhanced by integrating real-time hospital databases, electronic health records (EHR), explainable AI (XAI), multilingual support, and cloud-based deployment for remote ophthalmic screening and telemedicine.