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Neural Physics

Foundation physics for engineering

Building the foundation models of physics

We create high-fidelity simulation data and AI systems that capture real-world physics—from airflow over a vehicle to structural crash response—so you can design with confidence.

Our mission

Neural Physics builds foundation physics models and provides high-fidelity data and frontier AI to transform engineering design and simulation.

Full-stack AI for physical simulation

From raw data through deployment—one partner for your physics ML lifecycle.

  1. 01

    Data generation

    Curated, physics-grounded simulation data at the fidelity your problem demands.

  2. 02

    Foundation physics models

    General-purpose learned physics cores that encode dynamics across scenarios.

  3. 03

    Fine-tuning

    Adapt models to your geometry, materials, and operating conditions.

  4. 04

    Deployment

    Ship inference into your CAE, MLOps, or in-vehicle stack with clear SLAs.

Simulation data that matches the physics

Representative engineering domains we support.

  • Car aerodynamics

    Car aerodynamics

    High-fidelity flow fields and forces for external vehicle aerodynamics—ideal for surrogate modeling and design exploration.

  • Crash simulation

    Crash simulation

    Structural response and impact behavior from crush and safety simulations—calibrated for downstream ML and deployment.

Trusted by teams pushing simulation forward

Nvidia
Google
Microsoft
Siemens
Ansys
Toyota