The Project encompasses the industrial research aimed to timely and efficiently create and use airspace capacity, in combination with targeted, effective demand and/or capacity measures. As such, it will focus on advanced levels of dynamic airspace configuration, Leveraging different virtualization models, digital INAP applications as well as Network-wide monitoring, all with high levels of automation. The project addresses the R&I need for on-demand air traffic services reflective of traffic demand, and the continuity of ATM service despite disruption. The project exploits the latest advancements in artificial intelligence and machine learning, to supply a variety of supporting toolsets to ATM stakeholders that enable rapid exploration of options for the deployment of capacity-on-demand solutions, whenever and wherever required. The benefits include increased en-route capacity and improved cost-efficiency of ATS provision, without compromising the current safety levels.