The EINSTEIN project aims to develop automated algorithms for building performance optimization by integrating prediction, optimization, and fault detection capabilities into IES's building performance software. Funded by the EU for 4 years, the project partners IES and Trinity College Dublin to develop these algorithms. The EINSTEIN platform will use a building energy model, along with data from IES-SCAN, ERGON, and other sources, to enable model-based fault detection, as well as prediction and multi-objective optimization of building controls strategies considering comfort, economics, and carbon emissions. The integrated system aims to help reduce performance gaps between designed and operational building performance.