This video provides an overview of the installation process and a practical usage demonstration of EXACT, a user-friendly and extensible framework for anomaly detection. EXACT enables seamless data upload and supports anomaly detection using six different machine learning models. A key distinguishing feature of the framework is its integrated explainability support, which allows users to interpret ML model classifications through established XAI methods such as SHAP, LIME, and DiCE. Designed with modularity and openness in mind, EXACT facilitates reproducibility and future extensions. The source code is openly available on GitHub at https://github.com/TedBoman/EXACT.