Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{180902,
        author = {Devashish Potnis and Prathmesh Chavan and Abhishek More and Sudesh Patil and Dr. Swapna Bhavsar},
        title = {RESEARCH ON JINNY AI: AI FOR IMAGE, VIDEO AND AUDIO GENERATION},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {3652-3657},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180902},
        abstract = {This paper introduces the design and development of an AI-powered platform that can create high- quality images, videos, and audio based on natural language inputs. Building on the latest models like OpenAI and Replicate AI, the platform is centered around semantic interpretation of user inputs to generate contextually correct and creative multimedia outputs. Developed on modern web technology that consists of the MERN stack, Next.js, React, Tailwind CSS, Prisma, and Clerk Authentication, the system is accessibility, scalability, cost-effectiveness, and ease-of-use centric. In making more sophisticated AI technologies democratically accessible to the world, this research helps in unleashing more potent generative abilities upon more users beyond mere technology users. The paper examines the underlying framework, model amalgamation, system architecture, and prospective applications on a variety of industries, but emphasizes future areas of research work in improving AI- powered content generation.},
        keywords = {Artificial Intelligence, Image Generation, Audio Generation, Video Generation, Open AI, Replicate AI, MERN Stack, Next.js, React, Tailwind, Prisma, Cleark Authentication.},
        month = {June},
        }