Physics AI
Driftver trains surrogate models that reproduce the behavior of high-fidelity physics — structural, thermal, fluid, and electromagnetic — and evaluate it in seconds instead of hours or days.
From weeks of solving to seconds of inference
Traditional CAE relies on expensive solvers that limit how many designs a team can realistically evaluate. Driftver learns the underlying physics from your existing simulation data and replaces the solve loop with near-instant inference, opening up design spaces that were previously impossible to explore.
Validated against ground truth
We never ask engineers to take predictions on faith. Every surrogate model is benchmarked against high-fidelity simulation and, where available, physical test data. Accuracy and uncertainty are reported transparently so results can be used for real design and operational decisions.
Geometry-aware models
Predict fields directly on complex 3D meshes without hand-crafted feature engineering.
Quantified uncertainty
Every prediction ships with a confidence estimate, so engineers know when to trust it.
Continuously retrained
Models improve as new simulation and test data flows through the platform.
Ready to go deeper?
Talk to our team about embedding physics AI in your engineering programs.