Allbirds, the shoe company that practically defined startup-guy footwear, is now an AI infrastructure firm called Smartbird. According to TechCrunch AI, the company sold its shoe business for $43 million, raised another $100 million from the stock market, and just installed a new CEO, Nadia Carlsten, who started the job yesterday. Her first problem is a big one: she has a plan and a large pile of cash, but no team.
That detail is what stands out here. Smartbird is a public company with a fresh strategy and almost nothing built underneath it yet.
What actually happened
Allbirds pivoted to AI back in April. The playbook looked familiar to anyone who watched GameStop: take a struggling public company, attach it to the hottest trend, and ride the wave of retail investors piling in. It worked. The stock climbed, the shoe business closed, and the company rebranded.
Now Carlsten has to turn the story into an actual business. She’s a former AWS executive with an engineering PhD, and she most recently ran the European compute company DCAI. “We’re going to be recruiting a brand-new team for the AI business, and we’re going to be getting an office,” she told TechCrunch AI from Amsterdam. “The first task that I’m tackling right now is rounding up the leadership team.”
Treat it as a startup with a sole founder and an unusually large seed round.
The business model
Smartbird wants to be an AI infrastructure provider, but not the kind you might expect. It isn’t chasing the neocloud game of arbitraging chip prices against GPU time. Instead, Carlsten is targeting customers who need direct control over the servers running their models.
Think pharmaceutical companies, energy firms, banks, and government agencies. These are organizations that care more about data sovereignty than raw scalability, often for legal or business reasons. As TechCrunch AI reports, Carlsten sees her real competitor not as the hyperscalers, but as the internal projects companies build for themselves.
A few things define the approach:
- Small clusters, not mega-deployments. Customer needs sit in the hundreds to thousands of chips, not the massive GPU farms hyperscalers run.
- Control over price. Smartbird won’t win on cost, since the big clouds optimize chips around the clock. It’s selling agility and ownership of the stack.
- Modest timeline. Carlsten expects compute clusters deployed for several customers by the end of the year.
Why it matters
This is a real market, but a crowded and uncertain one. Hewlett Packard already offers single-tenant managed AI compute, and data center giant Equinix does too. The open question is whether managed, sovereign compute can grow the way cloud services have, where endless expansion is the whole point.
Compare Smartbird’s ambitions to the rest of the field. General Compute, an inference cloud, came out of stealth last month touting a $300 billion chip order. Carlsten says she doesn’t need commitments like that. “It’s not about large scales and huge numbers of GPUs,” she said. “They’re more about agility of these clusters, and more about having control of the infrastructure stack.”
That’s a more disciplined bet than most AI infrastructure pitches right now. Whether it’s a big enough one to justify a public company’s valuation is the part nobody can answer yet.
The fine print worth noting
When Allbirds pivoted, it dropped its public benefit corporation status, the charter meant to lock in the shoe company’s sustainability promises. PBCs are supposed to enshrine non-financial commitments. OpenAI, for instance, is a PBC focused on AI safety. Allbirds walking away from its own charter is a quiet reminder that those structures bend more easily than people assume.
Carlsten is being paid a $700,000 salary and roughly $9 million in stock to make this work, and she insists the move wasn’t a stunt. “It wasn’t, ‘Let’s just do AI, because it’s AI, and it’s hot,'” she told TechCrunch AI. “There are some companies out there chasing AI, but at the end of the day, what matters is, is there actual weight behind the chasing?”
The next few months will test that. Watch for who she hires to lead infrastructure operations and whether those first customer clusters land on schedule. Full details are available in the original TechCrunch AI report.