TAILORPLAST focuses on understanding and predicting plastic deformation mechanisms in intermetallic phases for advanced structural and functional materials. The traditional approach of manipulating microstructures in metal-based alloys has been immensely successful, but new materials and predictive materials design strategies are needed to enable new functionalities and sustainability in transportation, production, energy conversion and storage. TAILORPLAST seeks to address this challenge by adopting a generalised approach and leveraging recent experimental and computational insights into the atomic mechanisms of dislocation motion in intermetallics in combination with graph neural networks and their reach towards extensive databases. Recently, we could show that small changes in intermetallic composition can lead to dramatic property changes. We uncovered the details of the essential dislocation mechanisms and energy barriers in the intermetallic crystals and have demonstrated how this knowledge enables tailoring of properties. Within a single crystal structure, the critical stresses for deformation may be varied across a large range by inducing sublattice order, even in a binary intermetallic. The project's objectives are to expand the understanding of fundamental plasticity mechanisms beyond metals, transfer these mechanisms to a large class of topologically close-packed intermetallic phases, and ultimately identify promising intermetallics for tailored plasticity and predict the plastic properties of complex intermetallic precipitate phases in high-performance alloys. The success of TAILORPLAST will lead to purposeful application-oriented material selection, accelerated alloy design, and the ability to tailor structural materials for extreme conditions and functional materials for new applications.