Artificial intelligence systems are created for end users based on raw data received from the end users or obtained from any source. Training, validation and testing data is maintained securely and subject to authentication prior to use. A machine learning model is selected for providing solutions of any type or form and trained, verified and tested by an artificial intelligence engine using such data. A trained model is distributed to end users, and feedback regarding the performance of the trained model is returned to the artificial intelligence engine, which updates the model on account of such feedback before redistributing the model to the end users. When an end user provides data to an artificial intelligence engine and requests a trained model, the end user monitors progress of the training of the model, along with the performance of the model in providing quality artificial intelligence solutions, via one or more dashboards.