Self-service artificial intelligence platform leveraging data-based and physics-based models for providing real-time controls and recommendations

A method of optimizing an enterprise application, the method comprising:

• configuring a physics-based model using simulated data of the enterprise, wherein the physics-based model includes models of virtual sensors;
• generating independent variable values for a data-based model using the physics-based model when data is unavailable in a database, thereby enabling the data-based model to learn;
• building a baseline data-based model offline using the independent variable values generated by the physics-based model, wherein the baseline data-based model is trained without real-time field data;
• deploying the baseline data-based model at a client site, wherein the data-based model starts receiving real-time data from the enterprise application;
• and
• enabling the data-based model to self-learn once deployed at the client site, using the real-time data, thereby improving control readiness and optimizing enterprise outcomes.