Whether grid control and planning, the operational management of photovoltaic systems and storage facilities or their design: These and other tasks require load time series that map the increasingly dynamic consumption of many households far more accurately than standard load profiles. The Fraunhofer Institute for Energy Economics and Energy System Technology IEE and its partners in the SyLas-KI research project have therefore developed an AI-supported tool that can be used to create high-resolution synthetic load time series for numerous different consumers. They are indistinguishable from real measurement data in terms of their characteristics but meet all data protection requirements.