Imubit’s artificial intelligence platform provides instantaneous, closed-loop optimization of processes in heavy industries by integrating a dynamic process simulator, a reinforcement-learning neural controller, and performance monitoring dashboards. The dynamic simulator utilizes extensive historical plant data and is informed by fundamental principles to create a virtual representation of actual processes, facilitating what-if analyses regarding variable interactions, changes in constraints, and adjustments in operational strategies. Meanwhile, the reinforcement-learning controller, which has been trained offline using millions of trial-and-error scenarios, is employed to continuously optimize control variables, thereby enhancing profit margins while adhering to safety constraints. Real-time dashboards monitor the availability of the model, user engagement, and operational uptime, while also providing interactive visual representations of boundary conditions, operational limits, and trends in key performance indicators. Applications of this technology include synchronizing economic strategies with real-time operational data and identifying instances of process deterioration, ensuring enhanced efficiency and safety across operations. This comprehensive approach empowers industries to adapt swiftly and effectively to changing conditions.