PhysicsX

London AI engineering company that uses 'physics AI' to speed up the simulations engineers use to design aircraft, cars, chips and machinery.

About PhysicsX

PhysicsX builds AI for engineering. Engineers designing an aircraft wing, a car part, a chip or a wind turbine normally rely on computer simulations that can take hours or days to run for each design. PhysicsX trains AI models on physics so they can predict how a design will behave in seconds, which means engineers can test far more ideas and reach a validated design faster. The company calls its approach physics AI, and its platform is described as AI-native engineering.

PhysicsX is based in London, with offices in New York and Singapore and a growing presence in the Bay Area. It was co-founded by Jacomo Corbo, its chief executive, and Robin Tuluie, its chairman, together with Nico Haag, who leads simulation engineering. The company says it has more than 300 people, having doubled in the last twelve months. The pages we read do not describe the founders' backgrounds in detail.

The company's stated purpose is to make engineering tools keep pace with increasingly complex systems, which it says is a gap it exists to close permanently. It wants engineers to explore a much wider range of designs, to simulate in real time, and to move from concept to validated design faster.

Its platform is used in aerospace and defence, semiconductors, industrial machinery, automotive, energy and materials, and it also points to data centres as a sector under pressure to build better hardware quickly. It has launched specialist models for engineering, including LGM-Aero for aircraft design, and is developing larger pre-trained "large physics models". A distinctive feature is its forward-deployed engineers, who work alongside customers' teams on live projects. The company has been named in the Deloitte Technology Fast 50 for the UK.

PhysicsX looks for people who want to work on hard industrial problems, and says it provides the environment, tools and mission to do that. It is a good example of a career that combines engineering, physics and machine learning. The pages we read do not describe early-careers programmes, so students should check the careers page for current roles.

What they do

• {'desc': 'Physics AI that predicts how designs behave in seconds.', 'title': 'AI-native engineering platform'}
• {'desc': 'Larger pre-trained AI models for physics, in development.', 'title': 'Large physics models'}
• {'desc': 'PhysicsX engineers who work inside customer teams on live projects.', 'title': 'Forward-deployed engineers'}
• {'desc': 'Models such as LGM-Aero for aircraft design.', 'title': 'Aerospace engineering AI'}

Key facts

• Based in: London, UK, with offices in New York and Singapore
• Co-founders include Jacomo Corbo (CEO) and Robin Tuluie (Chairman)
• More than 300 people (company figure)
• Industries: aerospace and defence, semiconductors, machinery, automotive, energy, materials
• Named in the 2025 Deloitte Technology Fast 50

Website: www.physicsx.ai