In May 2026, Jonathan Godwin did what most researchers at elite AI labs never do: he turned down the safety of a prestigious job to build something the world had never seen. Godwin, who spent five years at Google DeepMind working on AI for science and advanced materials, left because he knew Google’s lab was never going to build an advanced-materials and hardware company itself. So he did it instead.
The result is Orbital Industries, a startup that just raised a $50 million Series B led by venture firm Plural, with Nvidia’s venture arm NVentures and prior backers Radical Ventures, Compound, and Fly Ventures joining the round. The 50-person team — split between London and San Francisco — is now on a path to ship the first AI-designed molecule to ever hit the commercial market, with a target date of 2027.
The Real Story Here
Orbital isn’t another AI drug discovery company or IP licensing play. Godwin built something structurally different from every other “AI for materials” startup in the field.
Most companies in this space find new chemical compounds with AI and then license the intellectual property to large chemicals or coatings companies like Germany’s BASF or Pittsburgh-based PPG. Orbital does the opposite: it uses AI to discover materials and then sells those materials directly — owning the full stack from atom to customer.
“We push the frontier of AI for science and engineering, but we’re what’s known as vertically integrated,” Godwin told Fortune. “We don’t sell that software. We have hardware, manufacturing and advanced materials teams, labs and things like that, and we use that software internally to develop new advanced materials and hardware devices, and sell those hardware devices.”
The company’s core AI model is called Orb. It predicts and simulates the quantum mechanical behavior of atoms — and Orbital claims it is the only model that can simulate 100,000 atoms on a single GPU while running roughly 10 times faster than alternatives released by Meta and Microsoft. A version trained on publicly available data is freely available, including through a multi-year partnership with Amazon Web Services. A proprietary version powers Orbital’s internal product work.
By the Numbers
- $50 million raised in Series B (May 2026), led by Plural
- 50 employees across London and San Francisco
- 100,000 atoms simulated on a single GPU by Orbital’s Orb model
- 10x faster than competitor models from Meta and Microsoft
- Traditional timeline for developing a new cooling fluid: 10 years and $100 million — Orbital did it in months
- 2027 target: first AI-designed molecule to reach commercial market in any industry
- $300 million seed round raised by competitor Periodic Labs; $100 million Series A raised by CuspAI — context for the scale of this space
Per Orbital Industries’ own press release, the Series B capital will fund commercial deployment of two initial products under its Orbital IT brand — both targeting data center infrastructure — and expand engineering teams across both offices. Future applications include energy, semiconductors, aerospace, and critical minerals.
The Hustler’s Library Take
The lesson every entrepreneur should pull from Orbital isn’t “raise $50M and go build an AI lab.” It’s about the business model decision Godwin made before he ever took a dollar of funding.
He looked at an entire category of competitors and said: everyone else is licensing. I’m going to own the end product. That single structural choice — vertical integration versus IP licensing — is the difference between building a services business with a ceiling and building an industrial company with a moat.
The same logic applies at every scale. The freelancer who delivers the final product beats the one who just provides the raw work. The founder who controls distribution beats the one who depends on someone else’s shelf space. Godwin’s ambition — to build “the largest industrial conglomerate” in Europe, an AI-native counterpart to the chemicals giants of a century ago — is big by design. “The reason that all those companies are old is because they have really entrenched moats,” he told Fortune. “In order to break down an entrenched moat, you need a pretty radical technology innovation.”
You don’t need to be building AI coolants for GPU racks. But if you’re in any industry where everyone else rents out their work and collects a margin, ask yourself what it would look like to sell the final thing instead.
What You Should Do
1. Audit your business model for licensing traps. Orbital specifically chose not to license its AI discoveries to bigger companies — even though that’s the easier path. Look at your own business: are you selling your capability to someone else who captures most of the value? If you’re a consultant, agency, or service provider, identify one deliverable you could package and sell directly instead of through a client relationship.
2. Build proprietary data before you build the product. Orbital’s competitive edge isn’t just the Orb AI model — it’s the proprietary training data that powers the version they keep for internal use. The public model is a distribution tool; the private model is the actual moat. Whatever business you’re in, figure out what data only you can collect, and start collecting it systematically today. The Data Room Playbook has a framework for documenting and protecting proprietary assets before you need them.
3. Find the “10 years, $100M” problem in your market. Godwin’s cooling fluid pitch is essentially: here’s a problem the industry has always solved slowly and expensively — we solved it fast and cheap. That’s the clearest product-market fit story that exists. Every industry has a version of this. Whop’s founders found it in digital commerce. The Emergent brothers found it in AI coding. Yours is somewhere — probably the thing your industry accepts as “just how long it takes.”
4. Use public tools to validate before going proprietary. Orbital made a public version of Orb available through AWS. This isn’t charity — it’s a distribution and validation strategy. If you’re building a product or platform, releasing a limited free version to developers, researchers, or early customers gives you real-world signal before you commit to the premium build. And if you’re at the early stage, NSF’s SBIR program is still one of the most underused ways to fund that R&D without giving up equity.
Source: Fortune — Orbital Industries Series B exclusive | Orbital Industries press release (primary source)
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