For this project, we are working with the Autonomous Formulation Lab (AFL) at the National Institute of Standards and Technology, a program that seeks to combine autonomous AI methodology and robotic hardware to discover and optimize new formations. The audience for their tools are individuals in academia and industry who want to discover and optimize formulations at labs across the country. An autonomous lab is a research laboratory that leverages the latest software, robotics, artificial intelligence, and other technologies to speed up work. Although sometimes, there may be a disconnect between research staffers and their tools in the form of files with hundreds of lines of code, or lengthy setup processes. To bridge the gap between researchers and developers, helping to speed up these labs, our team is providing technical support in two ways. Our first method of support is to improve the documentation for the AFL automation repository. Our goal is to make Tutorial and How-To Sections more user-friendly for people who don’t have as much programming experience. We will also implement a physical version of AFL-automation workflow using a Raspberry Pi to help us better understand the process and provide real-world examples to the documentation. Additionally, we are developing a user interface designed to assist researchers in creating and graphing stock solutions. The first page of the application allows the creation and saving of stock solutions with a variable number of components. Features also support editing, viewing, and searching of previously created solutions. The second page contains the subsequent graphing of component mixtures from the given stocks to visualize which combinations can be created. Dynamic settings allow the user to only see the inputs relevant to their desired graph, including sweeps or targets. The user interface connects to the existing AFL automation code, leveraging the functionality and logic already in use by the AFL.