Recent progress in Artificial Intelligence, especially in machine learning, has aroused unprecedented interest in these technologies. Many industrial sectors are now considering using them. However, this has led to strong scientific obstacles. Machine learning, especially deep neural networks, can perform well enough to consider critical applications such as autonomous vehicles, predictive maintenance, and medical diagnosis, but their theoretical properties are not well-known yet. These scientific challenges make it difficult to meet the industrial constraints required for a general application such as certification, qualification and explainability of algorithms. It is from these observations that the DEEL Project emerged in September 2017.

In early 2018, DEEL became transatlantic with the involvement of the CRIAQ (Consortium for Research and Innovation in Aerospace in Québec) and IVADO (The Institute for Data Valorization).