Artificial Intelligence (AI) is modern today. The application of the latest AI algorithms allow to identify and discover hidden information in large (or not so large) data sources (data lakes). When information is coming from Systems Engineering processes, the classical AI tools and technologies tend to fail, as the source of information does not necessarily have to be numbers. It can be textual requirements, model topologies, simulation policies or results, test cases scenarios. Risks, etc.
The SES ENGINEERING Studio ecosystem of tools allows interested customers to apply machine learning and information discovery within the Systems Engineering lifecycle, but during the standard operation of the engineers’ tools.