PhysicsX Raises $300M at $2.4B Valuation to Make Engineering Simulations Instant

Founders and Company Background

PhysicsX was founded by CEO Jacomo Corbo and Chairman Robin Tuluie, both veterans of Formula 1 racing engineering . The company is headquartered in London, with an existing office in New York and an expanding presence in the Bay Area and Singapore . The startup has more than 300 employees, a figure that has doubled over the last twelve months .

Commercial Traction

The scale of the round is underpinned by strong business momentum. PhysicsX reported that its recognized revenue doubled year-over-year while its booked revenue tripled . The company also more than doubled its customer count during the same period . Management pointed to AI data center hardware design as its fastest-growing segment .

How PhysicsX's AI Platform Works

PhysicsX has built an AI-native engineering platform designed to replace the traditional, time-intensive simulation workflows that dominate modern hardware development. Its software stack deploys AI models that can predict complex physical behavior in seconds rather than the hours or days—and in some cases months—that conventional physics solvers require .

This speed enables engineering teams to evaluate "orders of magnitude more design variants" and to embed physics-driven insight continuously across the entire product lifecycle . The company's models provide utility from early-stage conceptual design through detailed manufacturing process optimization, all the way to real-time digital twins operating in the field . Currently, PhysicsX serves customers in aerospace and defense, semiconductors, automotive, energy and renewables, industrial machinery, and advanced materials .

Where the $300 Million Is Going

According to the company's official announcement, the Series C capital is being allocated to three primary strategic priorities :

• Global Expansion: Scaling commercial operations and go-to-market presence, with particular focus on the United States and the Asia-Pacific region.
• Platform Expansion: Broadening the capabilities of its AI-native platform to cover additional engineering use cases and to penetrate new adjacent industries.
• Frontier Research: Developing a new generation of larger, pre-trained foundation models, which PhysicsX calls Large Physics Models (LPMs). These models are designed to learn from both synthetic simulation data and physical real-world sensor data, marking a step toward more generalized physics reasoning for industrial design and operations.

By training LPMs on a combination of simulated and empirical data, PhysicsX aims to create AI systems that not only accelerate design discovery but also close the loop between digital prototypes and the physical performance of machinery in operation, a step that could further erode the traditional wall between computation and testing in industrial engineering.