Leverages the largest curated property dataset for high-accuracy predictions through a choice of optimized models.
Quickly validates the suitability of new, cost-effective, stronger, and lighter materials for diverse applications.
Understand the complexities of minor composition changes to drive better application performance of trusted materials.
Improves the reliability of simulations by utilizing predicted material properties instead of typical values.
Lowers material testing costs by providing reliable property predictions, enabling focused and efficient testing programs.
Speeds up material selection, cutting down on project timelines.
Assess existing, approved, and trusted materials for use in other applications.
Saves on resources and increases efficiency by minimizing dependency on time-consuming physical tests.