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RANANO is an integrated artificial intelligence-based multimedia creation platform developed to combine multiple creative functionalities within a single web-based interface. The system addresses the fragmented workflow involved in using separate applications for image generation, image enhancement, video creation, animated text generation, and user guidance. RANANO uses a trained diffusion model for text-to-image generation, where the trained model checkpoint is integrated into the application for inference. The platform also incorporates image enhancement using super-resolution, video generation from selected images, animated text generation, and a voice assistant for interactive guidance. The system follows a modular architecture in which the frontend communicates with backend services responsible for model inference, image processing, multimedia generation, and output management. The diffusion model is trained using a prepared dataset, while the trained checkpoint is subsequently loaded during application execution without repeated training. Functional testing was conducted across the major modules, including checkpoint loading, prompt processing, image generation, image enhancement, video generation, animated text, voice interaction, output display and storage, and frontend-backend integration. All twelve test cases documented in the project were successfully passed. The results demonstrate that RANANO provides a unified and modular approach for AI-assisted multimedia creation while reducing the need to switch between multiple tools. The system also provides scope for future improvements in computational efficiency, processing time, and multimedia generation capabilities.