The AI-Native Engineering Platform

Our platform includes a range of model architectures that enable the development of highly accurate models across a wide variety of use cases. While model accuracy depends on both the specific application and the quality of training data, we often achieve strong results even with relatively low data volumes. As with all simulations, model outputs are approximations. However, unlike traditional numerical simulations, our models can integrate insights from laboratory and real-world data, enabling high accuracy even in scenarios where numerical methods fall short. All of our models feature uncertainty quantification, providing confidence levels alongside each result so outcomes can be evaluated in context. The platform also supports active learning — a live feedback loop that enables continuous retraining when areas of high uncertainty are encountered.

PhysicsX does not use customer data to train our pre-trained models.

The quantity of data required is highly dependent on the specific user case. However, Deep Physics Models can give accurate results even with low quantities of data. Both simulation and real-world data can be used to train our models, so depending on the context, little new data may be required. In addition, we have a growing number of pre-trained models, which can be fine-tuned with your private data, further reducing the amount of data required.

Absolutely. PhysicsX is purpose-built for complex, mission-critical engineering challenges. Our Delivery team works in close synergy with customers to tailor model architectures, simulation pipelines, and optimization loops to their unique context —whether that involves working with novel materials, unconventional geometries, or niche performance constraints.

Our platform is designed to integrate into your existing ecosystem without friction. We currently provide integrations for many industry-standard CAE tools like ANSYS, CATIA, and Siemens NX for CAD and OpenFOAM, Siemens Star CCM+ for simulation. New integrations can be easily developed allowing even bespoke tools and solvers to be integrated.

The PhysicsX platform is cloud-agnostic. We currently provide native support for AWS and Azure, while also ensuring the ability to deploy to hybrid or on-prem environments to harness existing HPC capacity and support high classification requirements.