PhysicsX is Accelerating Physics AI for Industrial Engineering with New Series C Funding

PhysicsX, a physical AI company on a mission to accelerate innovation and overhaul what engineering and manufacturing look like today, led by Robin Tuluie, Jacomo Corbo, and Nicolas Haag, has announced an oversubscribed $300 million Series C financing at a valuation of approximately $2.4 billion. The round is led by Temasek, with participation from new investors M&G Investments and Intrepid Growth Partners, alongside existing investors including Applied Materials, Atomico, General Catalyst, July Fund, NGP, NVIDIA, Radius, and Siemens. Temasek first invested in PhysicsX in 2025 and has played an instrumental role in supporting the company’s international expansion and growth.

Accelerating Hardware Development With AI.

PhysicsX is building an AI-native engineering platform designed to help industrial companies develop complex hardware faster and more efficiently.

The company focuses on industries such as aerospace and defense, energy, semiconductors, automotive, advanced manufacturing, and data centers, where product development relies heavily on simulation and engineering analysis. PhysicsX aims to address a longstanding challenge in these sectors: traditional simulation workflows are often slow, costly, and difficult to scale, creating bottlenecks in innovation and product development.

By combining AI with engineering and physics-based modeling, the platform seeks to accelerate design cycles, improve productivity, and help organizations bring new hardware to market more quickly.

Bringing AI To Industrial Engineering At Scale.

PhysicsX's platform uses AI models to predict physical behavior in seconds rather than the hours or days often required by traditional simulations. This allows engineering teams to evaluate far more design options and apply physics-based insights throughout the product lifecycle, from design and manufacturing to operational digital twins.

The platform is already deployed across aerospace, defense, semiconductors, industrial machinery, automotive, energy, and materials sectors. As advances in AI models and GPU infrastructure make physics-based AI practical at production scale, PhysicsX believes industrial adoption is reaching a major inflection point.

The company has experienced rapid growth, doubling recognized revenue, tripling booked revenue, and more than doubling its customer base over the past year. Its workforce has also grown to over 300 employees.

The new funding will support global expansion, further development of the platform, and research into larger pre-trained engineering models known as Large Physics Models, which are designed to bring foundation-model capabilities to complex engineering and manufacturing challenges.

Removing A Major Bottleneck In Hardware Innovation.

According to Jacomo Corbo, many of the world's most important engineering challenges, from aircraft and semiconductor design to energy systems and advanced manufacturing, are constrained by the speed at which engineers can analyze and apply complex physics.

He believes Physics AI can dramatically accelerate that process by allowing engineers to evaluate thousands of design possibilities in seconds rather than weeks. Beyond improving productivity, the technology aims to enable more efficient engineering, manufacturing, and operational workflows. The new funding will help expand access to these capabilities and support the development of increasingly powerful Large Physics Models for industrial applications.

Democratizing Advanced Engineering Simulation.

Robin Tuluie argues that while high-fidelity physics simulation has long been a cornerstone of engineering, it has traditionally been slow, expensive, and accessible only to specialized experts.

He believes Physics AI changes that by making advanced simulation faster and more scalable while combining physics-based models with real-world operational data. This allows engineers, designers, and operators across an organization, not just simulation specialists, to access sophisticated engineering insights and make better decisions. As adoption spreads throughout an enterprise, the value of these capabilities compounds across design, manufacturing, and operations.