Every speaker and microphone setup a user can configure has a unique sound. IR files can be used to digitally record the properties of said setups, which could then be applied to a guitar sample. The outcome is a recording that will sound as if it were recorded with the aforementioned configuration. If a user has a small library of IRs and wants to figure out which one of them sounds best with a guitar sample of theirs, it’s trivial to apply the few available IRs to the sample and decide which one sounds best. If the user’s IR library grows, however, it becomes increasingly difficult to figure out what combination of files is preferred. That’s why in this bachelor thesis, we’ll design a novel tool that allows a user to quickly and easily find an IR for their purposes despite having a vast library of them. Considering that whatever is considered the ’best’ IR for a purpose is subjective, the tools will allow the user to perform their goals exploratively. Guitar sample and IR combinations which sound similar should be grouped. To that end, we will gather many different low-level audio features, and apply dimensionality reduction so that in the visualization. To evaluate the successes and failures of the design, we’ll be making use of user studies. Feedback from these studies can then be used to refine the tool to better meet the needs of its intended users as well as discuss in what criteria the thesis failed and succeeded.