A new business wants to be one of Europe’s first “AI compute” hyperscalers, and it uses renewable energy as a big part of its pitch to potential users.
There is more demand than ever for “compute” because of the AI gold rush. “Compute” includes the processing power, infrastructure, and tools needed to do things like run algorithms, run machine learning models, and process data. The demand for GPUs (graphics processing units) and other AI gear has helped Nvidia a lot. It has grown into a $3 trillion powerhouse thanks to this demand.
Along with Nvidia, a whole industry of cloud infrastructure companies has grown, making a lot of money along the way. In the U.S., companies like Lambda and CoreWeave have sought to grow their server operations by raising huge amounts of money. Now, a Finnish company called DataCrunch is joining the fray. It calls itself one of the “few serious players” in the space and says that all of its operations are in Europe.
“GPU As A Service”
The CEO of DataCrunch started the company in 2020. Like its competitors, DataCrunch sells GPUs “as-a-service,” which it says will lower the cost of AI processing. The business said today that it has raised $13 million in seed funding, which includes $7.6 million in stock funding from investors like ByFounders, J12 Ventures, and Oskari Saarenmaa, co-founder of Aiven. The last $5.4 million in debt comes from Nordea and Local Tapiola.
It’s not common for a seed-stage business to raise so much money in the form of debt, but DataCrunch did it for the same reason that other companies in the same field, like CoreWeave, have been doing the same. The idea is to use physical assets, like Nvidia GPUs, as collateral for loans instead of giving away more stock.
This is also a better way to get large amounts of money because if things go wrong for DataCrunch, the banks can just take away the GPUs. People with a lot of money can do it without as much danger as, say, investing in a pure-play SaaS startup.
“Because of the type of business we’re in, our main costs for growth are driven by capex,” Bryon told Parhlo World. “This is the sensible thing to do, and as we grow, we’ll have more ways to get that money.”
With this new round of funding, DataCrunch has now raised a total of $18 million since its start. This will help the company build its infrastructure to handle Nvidia’s newest servers and clusters, such as the brand-new H200 GPU. That way, it will be able to get more customers, like business clients like Sony and AI researchers who work at places like OpenAI.
Bryon said, “That has always been a big market for us, and I think a lot of people have forgotten about this “person” market.” “It’s important to me because I sometimes use our services on the weekends and have since the beginning.”
In fact, independent researchers and developers who may only need a small amount of computing power for personal or school projects would be much more interested in flexible, on-demand prices.
“People who are studying for a Masters or a PhD — that’s a segment we want to stay connected to because it’s often people who are a few years away from doing something really great,” Bryon said.
Once they hit it big, you’ll be glad you hooked them up early. That’s the main point.
But all cloud companies have to deal with the huge problem that nobody wants to talk about: the huge amount of energy that is needed to power this AI change.
Green Machine
Part of DataCrunch’s “advantage” is the fact that its data centers are located in the Finnish capital, Helsinki, and Iceland — a country running on 100% renewable energy for years already.
Bryon said, “In Helsinki, we can sign up for green energy from the grid.” In one of our two Finnish data centres, the waste heat is being used to heat up Helsinki right now. The good thing about living in Iceland is that the air temperature is always low, and the grid already has 100% green energy. This means that Iceland is one of the best places in the world to do these kinds of things.
This is going to be very important to the company going forward. While it plans to offer its services to any company globally, it will mostly remain anchored in the Nordics and Iceland. “Perhaps in the future we’ll look at Canada if we can find suitable locations, where we can have a similar advantage in terms of carbon footprint of our operations,” Bryon said.
This “green” background is what DataCrunch hopes will also set it apart from other European competitors, such as FlexAI in France, which just came out of stealth mode with $30 million in seed funding, and Nebius, which just recently rose from the ashes of the Russian internet giant Yandex and is now a public company again.
There is a trade-off here, though: While low latency is often one of the big selling points for AI compute providers, DataCrunch isn’t necessarily going to be in that bucket, which means it will be better suited for a particular kind of workload.
“Our strategy is such that we’re not going to be the provider with the absolute lowest latency due to being in 100 locations around the world,” Bryon said. “We are more focused on the compute that doesn’t have that strict latency requirement. We can still have a decent enough latency though, it might not be 10 milliseconds, but it will still be something like 100 milliseconds.”
It’s also worth noting that DataCrunch’s data centers are in shared “co-location” facilities for now, but the company says it’s planning to start building out its own data centers in 2025 — something it will need significantly more capital for.
“I want us to be on a path toward going public with this company, and we’ll need access to plenty more capital to keep expanding the company,” Bryon said.
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