Here we introduce AIMSim, a Python package to make common cheminformatics tools available to endusers. AIMSim supports extremely versatile utilization, functioning as a Python package providing data structures and operations to support cheminformatics pipelines such as fingerprint generation, similarity searches, and clustering. At the same time, it also exposes a cross-platform tkinter-based Graphical User Interface (GUI) for complete code-free utilization. Morgan and RDKit's topological fingerprints are implemented. Additionally, we provide support for all molecular descriptors implemented in the mordred , PaDEL-Descriptor , and ccbmlib software packages, including hashed fingerprints and simple scalar descriptors. We implement 47 similarity measures, including all standard metrics used in cheminformatics, such as the Tanimoto similarity . Finally, we explore applications of AIMSim to homogeneous catalysis and organic synthesis. Additional case studies in machine learning using commonly referenced datasets are explored in the Supporting Information. The organization of the paper is as follows. In the first section, we discuss the design of the software, focusing on its task manager, Graphical User Interface (GUI) and its class structure. In the next section, we showcase AIMSim's functionalities. We describe the input data accepted and the various cheminformatics tasks that can be performed in AIMSim. Finally, we present two case studies using AIMSim on real chemical data.