One of the biggest challenges of Artificial Intelligence is its desperately needed transformation from a highly complex fabric of algorithms to a tool as simple as a hammer. Everyone must be able to use it independently of his/her academic background. Therefore, we explore the boosting of sustainable energy usage on the example of Testo data loggers, e.g., by live monitoring and state of charge prediction with survival algorithms. Moreover, we provide AI-assisted services such as the adaptive scheduling of maintenance intervals, the automated detection of ML model drifts as well as easy recalibration and retraining of models when necessary. In this context, our demonstrator also highlights concepts of intuitive interaction and visualization in order to reduce complexity of human interaction with Machine Learning and to empower domain experts to become self-determined AI users.