PhysicsX is building AIs to enable breakthrough engineering across advanced industries. These are a new class of AI-first digital engineering solutions that dramatically accelerate accurate physics simulation, enable generative engineering designs, vastly accelerate some of the most time-consuming activities in the engineering process, and make complex engineering more accessible. Taken together, they offer our customers a new frontier of optimization opportunities for engineering, manufacturing, and operations for complex machines.

PhysicsX is a deep-tech company of scientists and engineers, developing machine learning applications to massively accelerate physics simulations and enable a new frontier of optimization opportunities in physical design and engineering.  Born out of numerical physics and battle-hardened in Formula One, we help our customers radically improve their concepts and designs, transform their engineering processes and drive operational product performance. We do this in some of the most advanced and important industries of our time – including Space, Aerospace, Medical Devices, Additive Manufacturing, Electric Vehicles, Motorsport, and Renewables. We work at the edge of advanced CAE, physics simulation and machine learning, to solve our customers’ most difficult design and control problems.  Our work creates positive impact for society, be it by improving the design of artificial hearts, reducing CO2 emissions from aircraft and road vehicles, or increasing the performance of renewable turbines.   We are a rapidly growing company, profitable, sustainable and prefer to fly under the radar. We have trust-based relationships with our collaboration partners and customers and take great pride in guarding their confidentiality. At heart, we are engineers and as such are committed to the creed of continuous improvement: We aim for breakthrough innovations in established industries, have the gumption and pragmatism to see that ambition through to real-world implementations and believe strongly that there is always a better way.

AI:PHYSICSX

PhysicsX

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