The InToSteel project is a joint effort by Sapotech and Evertz to develop next generation abilities to improve the metallurgical processes of continuous casting and steel grinding, greatly exceeding the current state-of-the-art and enabling more sustainable processing. For continuous casting, novel automated process control methods are invented through integration of phenomena based heat transfer models (from Casim Oy) , predictive machine learning (from University of Oulu) and deep learning surface inspection analysis (Sapotech). In addition to improvements in continuous casting, novel grinding high precision practices are implemented via integration of high precision 3D measurements and deep learning based surface inspection of ground surfaces. This enables a next generation process optimization (spot grinding, high precision material removal optimization). The multi-disciplinary integration is performed at physical (mechanic) and logical (software+algorithms) levels, finally achieving a fully integrated solution. The integrated solution ultimately enables real time and predictive assessment of the continuous casting and grinding processes, ultimately enabling full automation of the processes.