London’s Orbital Industries bags €43 million to build industrial hardware from the atoms up

May 28, 2026 - 09:00
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Orbital Industries, a British company building industrial hardware from the atoms up using AI, has raised €43 million ($50 million) in Series B funding in order to scale their data centre products, grow its AI and engineering teams and develop its platform for industrial applications beyond data centres.

The round was led by Plural. Existing and previous investors, NVentures (NVIDIA), Radical Ventures, Compound and Fly Ventures also participated.

Jonathan Godwin, co-founder and CEO of Orbital Industries, says: “When people imagine a better future, they think about physical things: technologies that give them more freedom, more time, more life. AI will get us there faster. That’s what we set out to do at Orbital Industries.”

Orbital Industries’ Series B sits within a 2026 funding landscape in which capital has been moving into AI infrastructure, data-centre capacity, photonics, semiconductor tooling, industrial automation and AI-enabled materials science.

The most directly comparable UK examples include Nscale’s data-centre financing, Encord’s physical-AI data infrastructure round, Isembard’s software-powered factory expansion and Polaron’s materials-science AI raise.

Across 2026 funding rounds for AI infrastructure, EU-Startups tracked roughly €1.08 billion, although this figure is heavily influenced by large infrastructure and state-backed financings such as Nscale and CamGraPhIC. Orbital’s round is therefore sizeable for an industrial AI hardware company, but it is part of a broader pattern of investment into the physical layers needed to support AI deployment: compute, cooling, chips, energy systems, manufacturing and advanced materials.

“Frontier AI gives us PhD-level expertise across every discipline, meaning small, agile teams can move from materials discovery to commercial hardware in a way that simply wasn’t possible before, so what used to take a decade, we can now do in months. We’re starting with some of the most pressing challenges in data centres, but the scope of what this approach can unlock is much, much bigger,” adds Jonathan.

Founded in 2022, Orbital Industries designs, engineers and manufacturers physical infrastructure, using AI to accelerate how new technologies are discovered and brought to market.

It was co-founded by CEO Jonathan Godwin, who has been in AI research for nearly a decade, including five years at DeepMind working on AI for science, engineering and advanced materials design, alongside CTO James Gin-Pollock, a repeat AI founder who previously sold a company to Shutterstock, and COO Daniel Miodovnik, whose background spans finance, government AI and advisory work to the UN.

Instead of treating materials discovery, engineering and manufacturing as separate processes, Orbital integrates them into a single AI-driven system, enabling smaller, highly interdisciplinary teams to move faster and bring new industrial technologies to market more efficiently.

Orbital Industries’ goal is to apply this model to the physical economy, building the technologies needed to scale energy, compute and industrial systems.

The company is entering the market through Orbital IT, its commercial brand for data centre infrastructure – a $344 billion industry set to be worth more than $2 trillion by 2032. Rising AI compute demand and increasing GPU density are pushing infrastructure to its limits, with power, cooling and deployment emerging as the primary bottlenecks to scaling AI. These constraints will determine how quickly new systems can be built and deployed.

Ian Hogarth, partner at Plural, says: “AI progress is now constrained by the physical world: by energy, heat and infrastructure. Orbital Industries is tackling those constraints directly, from breakthroughs like its AI-designed cooling fluid, which enables the next generation of GPUs.

“The ability to discover and deploy these technologies faster than traditional industry will define the next phase of AI and it’s clear there is already strong demand for what the team is building.”

As AI models grow more powerful, the chips that run them generate increasing levels of heat in ever more dense environments, pushing conventional water-based cooling to its limits. Within the next few years, the company believes that new approaches will be required to prevent next-generation GPUs from overheating.

Orbital Industries has developed a dielectric cooling fluid and refrigeration system designed specifically for these chips; a breakthrough that enables future high-density compute. Unlike existing alternatives, the fluid is free from PFAS “forever chemicals”, allowing it to meet tightening regulatory standards across the US and Europe.

Traditionally, developing a new cooling fluid would allegedly take around a decade, but Orbital Industries says that their AI-led approach has “dramatically accelerated” this process. The company is working with leading data centre operators, including through a multi-year partnership with AWS, to develop cooling and efficiency technologies, bringing these systems closer to deployment at hyperscale data centres.

This is possible because of Orb, the company’s AI engine for simulating the quantum mechanical behaviour of atoms. Just as large language models have scaled to handle longer and longer documents, Orb has scaled to simulate larger and larger physical systems.

According to the company:

  • It is the only model that can simulate 100,000 atoms on a single GPU, where every competitor crashes.
  • It runs ten times faster than the nearest alternative – outperforming models from Microsoft, Meta and leading academic labs – turning week-long quantum simulations into coffee-break computations.
  • Independent benchmarks show its predictions don’t drift or hallucinate over time, meaning scientists can trust the results without babysitting the model.

In parallel, Orbital Industries has developed a modular data centre system designed using AI to solve the engineering challenges of extreme compute density required for next-generation GPUs. The system enables new AI infrastructure to be deployed in as little as six months, compared to traditional timelines of up to three years. Manufactured off-site and delivered as ready-to-deploy units, it allows data centre operators to bring high-density compute capacity online far faster at a time when demand is outpacing infrastructure supply.

Its long-term ambition is to apply the same model across sectors, including semiconductors, critical minerals, aerospace and energy, using AI to redesign how critical physical infrastructure is developed, manufactured and deployed.

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