BeyondMath, a London-based DeepTech company developing a generative physics model, has closed a €8.4 million ($10 million) Seed extension to double its headcount in 2026 and expand globally while increasing its research capacity.
The extension was led by Cambridge Innovation Capital, alongside existing investors including UP.Partners, Insight Partners, and InMotion Ventures. This closes the Seed Round at €15.7 million ($18.5 million).
Alan Patterson, CEO of BeyondMath, says: “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.”
In related coverage from EU-Startups in 2025–2026, Allonic raised €6 million in pre-Seed funding to develop its robotic body-manufacturing platform, reflecting investor appetite for hardware-centric physical-AI systems. Meanwhile, Nomagic secured €8.3 million to scale its AI-driven robotics deployments in the US, following an earlier €41.5 million raise in 2025 to expand its operations across Europe.
Combined, these disclosed rounds represent approximately €55.8 million channelled into adjacent physical-AI and robotics ventures, indicating sustained capital flows into applied AI systems that bridge software and industrial engineering – context that frames BeyondMath’s €15.7 million Seed round within a broader pattern of investment into AI-enabled physical and engineering technologies.
Edward Inns, Principal at Cambridge Innovation Capital, adds: “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.”
Founded in 2022 by AI industry veterans Alan Patterson and Darren Garvey, BeyondMath is innovating in Generative Physics, developing a foundational AI model trained on the fundamental laws of physics. By delivering a 1,000x acceleration in simulation speed, the platform overcomes the inherent limits of traditional solvers to reveal the physical breakthroughs of tomorrow. This reportedly compresses design cycles from months to minutes, potentially impacting industries like aerospace, automotive, and energy.
According to BeyondMath, engineering and industrial companies are struggling to design increasingly complex systems faster and more sustainably while using legacy simulation tools that often cannot cope with modern hardware and AI-driven workflows. B
eyondMath takes a new approach with a foundational AI model trained directly on first-principles physics. This enables engineering-grade simulations to be created in minutes rather than hours or days, delivering results up to 1000x faster than traditional supercomputing methods.
A key example of this impact is STRATA, a €16 million ($19 million), 3-year project with Honeywell, where BeyondMath will enable the simulation of hundreds of iterations for complex aircraft components. By optimising internal fluid paths and thermal performance, this partnership aims to accelerate the delivery of lighter, more efficient aerospace parts that have the potential to deliver billions of dollars in fuel efficiency savings while significantly reducing global aviation emissions.
In automotive engineering specifically – where BeyondMath works with an F1 team – the platform supports real-time testing of thousands of design combinations to identify optimisations in aerodynamics and thermal management. The company also has established partnerships with NVIDIA and AWS.
Read the orginal article: https://www.eu-startups.com/2026/02/uk-deeptech-startup-beyondmath-raises-e8-4-million-to-expand-generative-physics-research/
