BeyondMath secures seed funding to run simulations in seconds with generative physics
This article covers BeyondMath, an AI startup, which has closed £13.7m in a growth funding round to scale its foundational physics model and accelerate commercial deployment of a generative physics platform for engineering simulations. The funding is intended to expand research capacity, hiring and commercial rollout to support engineering teams in aerospace, automotive, data centre and semiconductor sectors by reducing simulation time and enabling faster design iterations.
BeyondMath, an AI startup, has closed £13.7m in a growth funding round to scale its foundational physics model and accelerate commercial deployment of what it describes as a generative physics platform for engineering simulations. The raise follows a £7.4m extension and will be used to expand research capacity, hire across the business and grow its customer base in Europe, the US and Japan.
Why it matters
Engineering teams building aircraft, cars, data centres and semiconductors face rising complexity and tighter sustainability targets, yet many still rely on legacy simulation tools that are slow and ill-suited to modern hardware and AI workflows. BeyondMath’s approach — a model trained on first principles physics rather than purely on data — promises to compress design cycles from days or months to minutes, potentially cutting simulation time by orders of magnitude and enabling many more design iterations within the same project timelines.
If those performance claims hold at scale, they could change how industries approach optimisation, materially affecting time to market, component weight and energy use — outcomes that map directly on to cost and emissions across aerospace and automotive supply chains.
Inside the product
BeyondMath has built a generative physics model it says is the largest of its kind, able to simulate phenomena ranging from aerodynamics to thermal management. The company reports benchmark results on the DrivAerML dataset showing substantially faster inference than traditional solvers and other machine-learning models, with acceleration claims of up to 1,000x versus conventional supercomputing methods.
A concrete application is the STRATA programme with Honeywell, a £14.1m three-year project in which BeyondMath will run hundreds of iterations for complex aircraft components in seconds rather than days. The company says this will allow optimisation of internal fluid paths and thermal performance, potentially yielding lighter, more efficient aerospace parts and large fuel-efficiency gains over fleet lifetimes.
Customers named in the announcement include major automotive, aerospace and electronics manufacturers, alongside players in data-centre design and semiconductor manufacturing. BeyondMath also cites an active collaboration with an F1 team for aerodynamic and thermal testing, and technical partnerships with NVIDIA and AWS to support model training and deployment.
Who are the investors?
BeyondMath’s latest extension was led by Cambridge Innovation Capital. The £7.4m Seed extension brings the round to a reported £13.7m (about $18.5m). Existing backers named in the announcement include UP.Partners, Insight Partners and InMotion Ventures.
Cambridge Innovation Capital is presented as a long-standing deeptech investor embedded in the Cambridge ecosystem; the firm manages more than £600m of capital and typically backs science-driven companies across AI, semiconductors, life sciences and quantum technologies. The investor statement frames the deal as support for a team combining physics expertise with modern AI techniques to tackle computationally hard engineering problems.
In the announcement, Edward Inns, Principal at Cambridge Innovation Capital, said:
BeyondMath is tackling one of the hardest and most valuable problems in engineering. By combining first-principles physics with modern AI, the team has built a platform that can redefine how complex systems are designed across multiple industries. We look forward to supporting Alan, Darren and the team as they continue to scale.
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Founder perspective
In the announcement, Alan Patterson, CEO of BeyondMath, said:
Engineering teams require ever-faster, more flexible simulation, but do not have the technology to deliver on these demands. Generative physics introduces a fundamentally new approach to engineering, unlocking innovation across fields ranging from aerospace and automotive to data-centre design. We now have the capital and investor support to accelerate our research roadmap and scale commercial adoption. This could be the ChatGPT moment for physics.
Patterson and co-founder Darren Garvey launched the company in 2022; the founders position the product as an engineering-grade alternative to traditional solvers, intended for integration into design workflows where speed and fidelity are both required.
The bigger picture
BeyondMath sits at the intersection of two venture themes: applying large foundational models beyond language and image tasks, and the industrialisation of AI for engineering workflows. The company’s partnerships with hardware and cloud providers and collaborations with incumbents such as Honeywell and an F1 team are typical of deeptech firms seeking both technical validation and route-to-market through strategic customers.
The deal also signals continued appetite from AI investors for applied, capital-efficient companies that can demonstrate material cost or emissions improvements for industrial clients. The outcome to watch is whether generative physics models can sustain accuracy and reliability across diverse, safety-critical engineering problems where validation standards are high.
This raise underscores the UK’s strengths in deeptech and physics-informed AI, particularly around Cambridge and London, and reflects ongoing investor interest in commercialising advanced simulation technology across Europe and global manufacturing hubs.
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