Test and expand the capabilities of the Zetane software for application in complex artificial intelligence industrial (AI) projects with the objective of augmenting the users’ ability to gain new insights in model performance and gain more trust on how the data influences the AI models to arrive at the AI’s recommendations. The project will involve reviewing the state-of-the-art solutions in this field and proposing and implementing recommendations on how to more efficiently identify areas of concern or improvement, ensure useful metrics are provided as part of the output to the users, validate explainability approaches and recommend new functionalities necessary. This project arrives at a critical time for Zetane because the intern will be directly involved in helping the company make key improvements in the Zetane engine; especially in the validation of complex AI models’ validation and explainability.