Beyond human imagination
For decades, industrial innovation has been determined by human imagination and engineering intuition working in concert with traditional numerical simulation tools to shape our industrial world. From designing the wings of a Boeing aircraft to next-generation wafers or optimising the energy efficiency of Formula 1 vehicles, these simulation tools have enabled engineers to understand and iterate on complex systems. However, the traditional numerical simulation process to date has been one of educated assumptions, computational boundaries, siloed data and cycles of trial and error: powerful but limited by the tools available and the cognitive bandwidth of even the most brilliant engineers. The result is an asset lifecycle measured in years if not decades in which the cost of iteration is massive and the rate of innovation is continuously throttled.
But AI is now transforming what is possible. What if we could use AI and advances in numerical inference, large physics and geometry foundation models trained on the physics of the world and the geometries of industrial components, to simulate, optimise and even design anew the most complex engineered systems?
Picture a semiconductor fab line accelerated by AI-driven thermomechanical simulations reducing cycle times from five to two years and less, or a next-generation EV whose aerodynamics and structure are continuously refined by models that learn from every iteration across the asset lifecycle. This future has already arrived. We are at the dawn of a new paradigm redefining what is possible in engineering, one which is being built by PhysicsX
PhysicsX is founded by Robin Tuluie, former Head of R&D at Renault (Alpine) F1 and Mercedes GP and Vehicle Technology Director at Bentley Motors, and Jacomo Corbo, former Chief Scientist and Co-Founder of QuantumBlack (AI by McKinsey) and former Chief Race Strategist at Renault (Alpine) F1. The company is building a developer-first AI platform for software-driven engineering, enabling organisations to rapidly develop, deploy, and scale AI-powered applications across the entire product lifecycle. By shifting from traditional numerical simulation to AI-driven inference, the PhysicsX platform delivers orders-of-magnitude speed improvements, integrates numerical and experimental data to go beyond first-principles physics, and extends high-fidelity simulation to previously inaccessible applications across the engineering lifecycle.
The opportunity is urgent. As the global economy seeks productivity gains in the face of supply chain fragmentation, material constraints and skills shortages, engineering-led industries from aerospace and automotive to semiconductors and materials, need a step change in efficiency.
PhysicsX not only possesses world class AI and simulation capabilities, they bring a deep understanding of the complex systems and processes with which their customers operate.
With PhysicsX already in use across multiple verticals - from semiconductors to materials - Jacomo and Robin know all too well engineers do not work in isolation: the engineering process spans some of the largest organisations in the world, global supply chains, a patchwork of compliance regimes, and continuously evolving digital toolchains. Building this future is a full stack challenge. It demands a rare combination of deep learning researchers, physics and simulation experts, software engineers who can scale infrastructure, as well as commercial leaders who can navigate complex enterprise sales and partnerships
Indeed, PhysicsX’s technology is already embedded in the workflows of some of the world’s most sophisticated engineering organisations, solving high-stakes, real-world problems in the most demanding environments.
The next generation of engineering platforms must be enterprise-grade, fully integrated with existing workflows, and developed in close collaboration with major industrial players, precisely as PhysicsX is doing. Only then can we unlock value not just for individual engineers, but fully refactor engineering workflows to accelerate innovation and systematically drive greater efficiency and productivity across critical industries.
That is why we are proud to lead this $135m Series B investment in PhysicsX alongside Temasek, Siemens and Applied Materials. Jacomo, Robin and their team stand at the intersection of foundational AI research and engineering with deep industrial know-how. With models trained across domains, scales, and geometries, and a platform able to support engineering workflows end-to-end , PhysicsX is fundamentally changing the way we innovate and build. In this new paradigm, we are rapidly moving from what is imaginable to the frontier of the possible.
