Achieve superior simulation accuracy with AI-driven materials intelligence. Seamlessly manage, model and simulate complex material behavior from raw test data to validated, simulation-ready solver material cards ensuring full traceability, compliance and engineering confidence across the enterprise.
Discover how material scientists and engineers can:
Accurate simulation begins with trusted data. Eliminate data silos and manual lookup with a centralized, AI-powered material database. Access validated datasets and simulation-ready solver material cards across structural, fatigue, thermal, manufacturing and electromagnetic domains - so you spend less time searching and more time simulating with confidence.
Raw test data alone cannot drive simulation. Engineers need validated material models that accurately reflect real-world behavior. Automated curve-fitting, extrapolation and model calibration workflows transform test results into simulation-ready material cards - supporting nonlinear, hyperelastic and rate-dependent behaviors, reducing manual effort and ensuring consistency between physical and virtual inputs.
Composites and heterogeneous materials behave differently at every scale. Capturing that complexity accurately, without sacrificing computational efficiency is essential for reliable structural simulation. Using Reduced Order Modeling with 3D FEA unit cells, engineers can develop predictive material models that bridge micro-scale material physics with macro-scale structural performance across leading solvers.
Physical testing alone cannot keep pace with the speed of modern product development. Data gaps, anomalies and untested variants slow qualification and increase risk. Integrated AI and machine learning tools analyze existing datasets to predict material properties, recommend optimal models and accelerate qualification, enabling faster innovation with fewer physical tests and more sustainable material decisions.
Material data created in isolation cannot support decisions across engineering processes. Teams need a connected, traceable flow of material intelligence - from supplier data through characterization, modeling and virtual validation. A unified materials digital thread ensures consistent material definitions, secure collaboration and full regulatory traceability from early design to production.
