A technology component that facilitates the secure, efficient, and collaborative training and sharing of machine learning models, combining Distributed Machine Learning, Federated Machine Learning and Trusted ML Model Sharing. It provides a controlled environment for creating and sharing ML models while ensuring trust, accountability, and compliance. During training, large-scale tasks are distributed across multiple systems to enhance computational efficiency, while decentralized devices train models locally and share updates to protect data privacy. This scalable and interoperable hub fosters collaboration between diverse participant whilst upholding data sovereignty. It also enables participants to co-create and deploy innovative machine learning solutions effectively.