The high cost-effectiveness of profiling processes is often offset by a high adjustment effort of the equipment. In industrial practice, the fine adjustment of the forming stands is based on the experience of skilled workers. Problems here lead to increased scrap and can result in long downtimes. By integrating sensors into the equipment, artificial intelligence approaches are being implemented at PtU in the form of assistance systems. Information obtained about the process forces and drive torques is related to the profile quality and the energy requirements of the process. From this, on the one hand, the necessary adjustment measures can be formulated for the skilled worker, so that the high material utilization rate is maintained without waste and scrap, even with complex profiles and frequent variant changes. On the other hand, continuous process monitoring enables the detection of tool rolls that are too fast or too slow and work against the continuous profile feed. Measures derived from this, such as freely rotatable roll segments, fine adjustments of the profiling gap or targeted local adjustment of tribological properties, increase the energy efficiency of the process.