PhysicsX
PhysicsX accelerates engineering design cycles through AI-powered physics simulation.
PhysicsX is a physics AI platform that accelerates engineering and manufacturing by combining AI-driven multiphysics inference with numerical simulation. The platform reduces simulation run times from hours to seconds and enables engineers to run 100,000 simulations in a day versus weeks with traditional methods. Built by former Formula 1 engineers, it integrates with industry-standard CAE tools like ANSYS, CATIA, and Siemens NX, spanning design, manufacturing, and operations across multi-physics domains.
Problem solved
Engineering teams spend weeks on each design iteration due to computationally expensive simulations, slowing product development and limiting optimization exploration.
Target customer
Large enterprises in automotive, semiconductor, aerospace, mining, and advanced manufacturing needing to optimize product design and reduce simulation time.
Founders
J
Jacomo Corbo
CEO & Co-Founder
Former Chief Scientist and Co-Founder of QuantumBlack (AI by McKinsey), Chief Race Strategist at Renault F1, and partner at McKinsey & Company with PhD in Computer Science from Harvard School of Engineering and Applied Sciences.
R
Robin Tuluie
Co-Founder & Chairman
Theoretical physicist who served as Head of R&D at Renault (Alpine) F1 and Mercedes F1, and Vehicle Technology Director at Bentley Motors managing 30+ digital prototypes.
N
Nicolas Haag
Co-Founder & Director of Simulation Engineering
Automotive and motorsport engineer who worked at Mercedes-Benz, Audi Sport, and Bentley Motors before co-founding PhysicsX in late 2019.
Funding history
Series A
$32M
November 2023
Led by Unknown
· Unknown
Series B
$135M
June 22, 2025
Led by Atomico
· Temasek, Siemens, Applied Materials, July Fund, General Catalyst, NGP, Radius Capital, Standard Investments, Allen & Co
Series B Extension
$20M+
November 19, 2025
Led by NVentures (NVIDIA)
· NVIDIA committed up to $100M total across this and future rounds
Total raised:
$170M
Pricing
Not publicly available. Enterprise B2B delivery model with custom implementations.
Notable customers
Rio Tinto, Siemens, Applied Materials, Microsoft
Integrations
ANSYS, CATIA, Siemens NX, OpenFOAM, Siemens Star CCM+, NVIDIA Industrial AI Cloud, Deutsche Telekom
Tech stack
jQuery (JavaScript libraries)
core-js (JavaScript libraries)
Open Graph
Webflow Ecommerce (Ecommerce)
Google Analytics (Analytics)
Google Font API (Font scripts)
Apple iCloud Mail (Webmail)
Microsoft 365 (Email)
Google Hosted Libraries (CDN)
Webflow (Page builders)
Amazon Web Services (PaaS)
Website
Competitors
World Labs
Broader generalist physics AI approach, less focused on engineering CAE integration.
Luminary Cloud
Competing physics simulation acceleration platform with different technical architecture.
ToffeeX
Alternative physics-informed AI solution with different market positioning.
Why this matters: PhysicsX represents a paradigm shift in engineering simulation, backed by $170M in funding and partnerships with NVIDIA, Siemens, and Applied Materials. The founding team's Formula 1 engineering pedigree combined with cutting-edge physics AI positions it to reshape how the world designs and manufactures complex products at scale.
Best for: Large manufacturers and engineering firms that need to dramatically reduce design iteration time and explore vastly more optimization scenarios without massive compute costs.
Use cases
Semiconductor Equipment Prototype Development
PhysicsX helps semiconductor manufacturers like Applied Materials significantly reduce the time required to develop new equipment prototypes by running thousands of thermal and fluid dynamics simulations in parallel instead of sequential weeks-long simulations.
Consumer Electronics Thermal Optimization
Applied to Microsoft Surface devices, the platform optimized thermal behavior by enabling rapid iteration and testing of thermal designs, reducing design cycles from weeks to days.
Mining & Metals Process Efficiency
Working with mining operators like Rio Tinto, PhysicsX optimizes copper extraction efficiency by simulating complex hydrometallurgical processes, potentially increasing recovery rates from 40% to 80% through rapid design exploration.
Alternatives
Traditional CFD/FEA Software (ANSYS, COMSOL)
PhysicsX accelerates these by 100x+ through AI surrogates while maintaining physics fidelity; traditional tools run single high-fidelity simulations in hours or days.
Luminary Cloud
Similar physics simulation acceleration but different technical approach and market positioning.
FAQ
What does PhysicsX do? +
PhysicsX is a physics AI platform that combines deep learning with physics-informed models to accelerate multiphysics simulation. It reduces simulation runtimes from hours to seconds and enables engineers to run 100,000 simulations in a day instead of weeks. The platform integrates with standard CAE tools and spans the full engineering lifecycle from design through manufacturing and operations.
How much does PhysicsX cost? +
Pricing is not publicly available. PhysicsX operates an enterprise B2B delivery model with custom implementations. Contact the company directly for pricing information.
What are alternatives to PhysicsX? +
Traditional CFD/FEA software like ANSYS and COMSOL provide high-fidelity simulation but lack AI acceleration. Competitors like World Labs, Luminary Cloud, and ToffeeX offer physics AI solutions with different technical approaches and market focus.
Who uses PhysicsX? +
PhysicsX serves large enterprises in automotive, semiconductor, aerospace, and advanced manufacturing. Notable customers include Rio Tinto, Siemens, Applied Materials, and Microsoft, using the platform to optimize product design and manufacturing processes.
How does PhysicsX compare to traditional simulation software? +
PhysicsX accelerates simulation by 100x+ by replacing traditional solvers with physics-informed AI surrogates that maintain credibility through conservation law constraints. While traditional software runs single high-fidelity simulations in hours, PhysicsX enables thousands of parallel simulations in seconds, fundamentally changing how engineers approach design optimization.
Tags
physics simulation
multiphysics
AI inference
engineering optimization
CAE integration
manufacturing
design acceleration
enterprise AI