This article presents a real‐time software platform (the GALENO platform) that was designed to support the development of algorithms to automate anesthesia procedures. Automation of anesthesia can contribute to improve the anesthesia practice, by personalizing health care, and by allowing the anesthesiologist to concentrate on supervisory tasks, avoiding repetitive manual work that can be executed and optimized by using automatic control systems. The GALENO platform is used for rapid prototyping of new control algorithms applied to anesthesia and was developed to be used by medical staff as a supporting tool for general anesthesia in a clinical setting. It has been tested in simulation and in real clinical settings. The platform can control the administration of several anesthetic drug combinations for total intravenous anesthesia using the DoA/BIS index and the NMB level, during induction and maintenance phases. To highlight some of the main features of the platform, and its practical results, two control algorithms are used as examples, the closed‐loop predictive min–max target controlled infusion is described and is used to control DoA/BIS, and a self‐tuning proportional‐integral‐derivative is used to implement the control of the NMB.