Many of today's office buildings suffer from inefficient energy management caused by missing, outdated, or fragmented systems. This results in unnecessary energy consumption and increased operating costs.

In a test phase lasting several weeks, triebwerk.ai installed over 200 sensors that recorded data on heat, humidity, lighting and movement. This data was then analyzed by the data science team to identify recurring patterns and anomalies. Based on these findings, the engineering team developed a prototype (MVP) with a real-time dashboard and an AI algorithm to predict space usage.

The introduction of the MVPs enabled a transparent presentation of the collected data and an effective prediction of the use of space. This solution immediately identified defective temperature controllers and prevented faulty heating and lighting periods in the medium term, which led to a significant improvement in energy efficiency. As a result, operating costs were reduced and the ecological footprint was reduced.