How an e-scooter founder raised $5 million to build space data centers

Here’s one metric for tracking SpaceX’s IPO later this week: The company has changed the venture industry’s perspective on long-term, capital-intensive space so much that a talented founder with no space experience can fund a space data center company.

Orbital, a new firm that emerged in May from a16z’s startup accelerator program Speedrun with a $5 million seed round, is the latest company promising to do inference in space — just as soon as Starship is flying regularly. Other investors include Basis Set, Human Element, Wayfinder, Antler, Anti Fund, Ascent, Rubik, Zero Knowledge Ventures, LYVC, Feld Ventures, New Legacy, FNDR, UpHonest and Asterisk.

Founder and CEO Euwyn Poon previously founded e-scooter company Spin in 2017 and sold it to Ford a year later, joining the automotive giant. When he was ready to start a new company, a16z’s Speedrun was eager to get on board, according to partner Andrew Chen, who told TechCrunch that Poon worked through several ideas before landing on space data centers.

You’re familiar with the pitch. There’s insatiable demand for AI compute, and deploying it is slow going on Earth. Why not head to space for limitless sunshine and limited environmental reviews? The main problem is the brutal economics of launching stuff into orbit, which currently leaves the business case unable to close.

Orbital, like many of it competitors, is betting on SpaceX figuring out its Starship rocket and offering it to commercial customers. “We will get to full scale when Starship comes online,” Poon explained. The price of the Falcon 9, the current state of the art, “makes this not economically feasible.”

For now, Poon and company — which includes about a dozen folks in Los Angeles, with experience at Amazon LEO, SpaceX, and Northrop Grumman — are working toward a demo flight that will see the company fly an Nvidia Blackwell chip on a partner’s satellite to test Orbital’s radiation shielding and thermal management tech. In 2028, the company hopes to launch its first data-processing spacecraft with Nvidia’s Space-1 Vera Rubin-class GPUs.

At that point, the company wants to start doing piece-wise inference work, which would allow it to generate revenue with each satellite launched. That’s a similar path to rival data center start-up Starcloud, which already has a GPU in orbit and plans to launch several more to generate income until Starship enables them to deploy their full constellation.

Orbital’s goal is to deploy 10,000 satellites that provide a distributed gigawatt of computing power, with each satellite providing 100 kw of power. For comparison, Elon Musk said SpaceX expects its AI satellites produce up to 150 kw, and Starcloud expects to field larger 200 kw-rated spacecraft to run chips.

Some companies are too impatient to wait for Starship. Cowboy Space Company, another space data center startup backed by a16z, recently decided to start building its own rockets. Jeff Bezos’ space company Blue Origin also announced plans to launch data centers into space using its New Glenn launch vehicle.

Poon is confident that the breadth of AI demand will allow many companies to succeed. “There’s so many lanes for companies in our space to pursue,” he told TechCrunch, before rattling off an array of choices that included companies pursuing different AI workloads, designs, and concepts of what an space data center looks like.

Chen said that Poon’s experience scaling up a company that deployed 250,000 scooters across 100 cities shows he can manage the tricky task of building an aerospace company. Over the long term, a project like this might take a decade and $5 billion or more, but Chen said venture firms are more comfortable with timelines like that.

“This kind of thing would have sounded crazy 10 years ago when we were all building mobile apps,” he said. “Starting it in 2026 just lets you tap into all the energy and excitement that’s that’s happening in the capital markets.”

Poon found his way into the space data center business by a circuitous route. After leaving Ford, he bought a Nvidia A100 on a lark, co-locating it in a Santa Clara data center and serving open-weight models. That first-hand experience convinced him the value in delivering compute in the era of AI.

Now he’s just got to put a couple thousand GPUs in space.