Machine Learning (ML) and Artificial Intelligence (AI) have come to the forefront of data analytics with the promise of generating new medical insights. However, for healthcare data, patient data security is paramount due to the GDPR and similar regulations. Traditional methods of data consolidation for Machine Learning/AI modelling into a single warehouse or a data lake are often not possible even with anonymised data due to data protection rules. Douglas Drake at Clinerion Ltd. demonstrates how this ensures data security within the original data domain while allowing analytics for modelling and AI to be applied in a federated fashion.