Orbital Industries has raised USD $50 million in a Series B funding round led by Plural.
Other investors included NVentures, Nvidia’s venture arm, along with Radical Ventures, Compound and Fly Ventures. The funding will support wider commercial deployment of Orbital’s data centre products, hiring in London and San Francisco, and development of its AI system for other industrial applications.
The London-based company develops hardware for AI infrastructure. Its first products are a modular data centre system and a cooling fluid for dense GPU environments, both of which have become pressure points as demand for AI computing rises and newer chips generate more heat.
Orbital’s modular data centre product is designed to cut deployment times to as little as six months, compared with conventional projects that can take up to three years. The system is manufactured off-site and delivered as ready-to-deploy units, with SLB as Orbital’s manufacturing partner.
The company has also developed a dielectric two-phase cooling fluid for current and next-generation GPUs. It says the fluid is non-toxic and free from PFAS, a class of chemicals facing tighter scrutiny and possible restrictions in the US and Europe.
Data centre focus
The business is entering the market through Orbital IT, its brand for data centre infrastructure. It is targeting operators, sovereign AI programmes and companies that want to bring high-density compute online without building large internal engineering teams.
Orbital is also working with data centre operators through a multi-year partnership with AWS to develop cooling and efficiency technologies. The aim is to move its systems closer to use in hyperscale facilities.
The company was co-founded by Chief Executive Officer Jonathan Godwin, who previously worked at DeepMind on AI for science, engineering and advanced materials design, with Chief Technology Officer James Gin-Pollock and Chief Operating Officer Daniel Miodovnik. Orbital employs about 50 people across London and San Francisco.
At the centre of the company is Orb, an AI model used to simulate the quantum mechanical behaviour of atoms. Orbital says the system shortens the time needed to discover and test new materials, including those used in cooling systems, compared with traditional development cycles.
The approach reflects a broader push by AI companies to move beyond software and address the physical constraints shaping the sector. As AI models grow and data centres become more power-intensive, limits in cooling, power supply and construction speed are becoming a commercial issue for cloud providers and operators.
Orbital sees those constraints as an opening to build industrial products rather than only software tools. It has said it intends to apply the same model beyond data centres in areas such as semiconductors, critical minerals, aerospace and energy.
For investors, the pitch is that growth in AI infrastructure will depend not only on better models and chips, but also on faster deployment of the physical systems around them. In that context, companies that can reduce build times or offer alternatives to regulated cooling materials may find a market among operators trying to expand capacity.
“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. 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. 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,” said Jonathan Godwin, Co-Founder and Chief Executive Officer of Orbital Industries.
Plural said Orbital is addressing a growing bottleneck in the AI economy. “AI progress is now constrained by the physical world: by energy, heat and infrastructure. Orbital Industries is tackling those constraints directly, including through breakthroughs such as 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 there is already strong demand for what the team is building,” said Hogarth.
