Our project's main goal was to create a web application that enables visualization and inverse analysis of Small Angle Scattering data using pre-trained machine learning models. Part of that goal was ensuring the application we wrote was reponsive, easy to use and understand, performed well on all manner of machines, and has a flexible codebase for future expansion. We accomplished these goals by developing SASGUI, a responsive web-based application with a React TypeScript Frontend, Python Backend, and SQLite database. Headline features include a real-time reactive Small-Angle-Scattering curve graph, capable of displaying uploaded experimental data alongside simulated Small-Angle-Scattering curves that can be generated by adjusting responsive parameter sliders. SASGUI also has the ability to predict the morphology (shape) and structural parameters (dimensions) of nanoparticles by analyzing Small-Angle-Scattering data with a machine learning model, a standout feature for research applications. Finally, SASGUI allows users to save and load application state, which could be used to save work, or to create templates for use in the classroom or the lab.