In the rapidly evolving domain of image processing, the conversion from RGB to hyperspectral imaging represents a significant leap forward, offering unparalleled depth and accuracy in image analysis with a lower cost. This paper introduces a novel Software-as-a-Service (SaaS) framework that revolutionizes this transition, making hyperspectral imaging more accessible and efficient for various applications. We propose an advanced Deep Learning algorithm that seamlessly converts standard RGB images into hyperspectral data, leveraging cloud and edge computing to enhance processing power and scalability. This method not only democratizes high-end imaging technology for broader use but also significantly reduces the cost and complexity traditionally associated with hyperspectral imaging. Our analysis shows that our SaaS platform is much easier to use than traditional hyperspectral image acquisition techniques. Additionally, it clearly demonstrates how a software-centric approach reduces acquisition time.