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DataCrunch wants to be Europe’s first AI cloud hyperscaler – powered by renewable energy

The new startup is preparing to become one of the first “AI” hyperscalers in Europe, with renewable energy playing an important part in its appeal to prospective customers.

The AI ​​goldrush has fueled an unprecedented demand for “compute,” which refers to the processing power, infrastructure and resources needed for tasks such as running algorithms, running machine learning models, and processing data. One of the main beneficiaries of this demand has been Nvidia, emerging as a three billion powerhouse behind the demand for its GPU (graphics processing units) and related AI hardware.

In parallel, the cloud infrastructure provider industry has sprung up behind Nvidia, raising a lot of cash along the way. In the US, we’ve seen the likes of Lambda and CoreWeave reach multi-billion dollar deals to expand their data center operations. Now, Finnish startup DataCrunch is throwing its hat into the ring, presenting itself as one of the “few key players” in the space with all operations in Europe.

DataCrunch team in Finland. Photo credits:DataCrunch

‘GPU-as-a-service’

Founded in 2020 by CEO Ruben Bryon, DataCrunch — like its peers — sells GPUs “as a service,” promising to reduce AI processing costs. The company today said it has raised $13 million in seed funding, including $7.6 million in equity financing from backers such as ByFounders, J12 Ventures, and Aiven founder Oskari Saarenmaa. The remaining 5.4 million loans come from Local Tapiola and Nordea.

While it’s rare for a seed-stage startup to raise as much debt, DataCrunch did so for the same reason that others in the space, such as CoreWeave, have also been raising debt levels. It’s all about using physical assets – eg Nvidia GPUs – as collateral to secure the loan, rather than providing more equity.

It’s also very efficient to secure large buckets of money this way, as banks can just take the GPUs if things go well with DataCrunch. For those who control the purse strings, it is more risky than investing in a pure SaaS startup, for example.

“Given the business we are in, our biggest cost to grow is capex [capital expenditure] it’s driven,” Bryon told TechCrunch. “This is a sensible way to go about it, and as we grow, more access to those funds becomes available.”

This new round takes DataCrunch’s total funding raised from the start to $18 million, and will go some way toward helping it build the infrastructure to support Nvidia’s latest servers and clusters, including the shiny new H200 GPU. In turn, this will help it grow its customer base to include not only corporate customers like Sony, but individual AI researchers working on the likes of OpenAI.

“That has always been an important market for us, and I think this ‘individual’ market has been left behind by many,” Bryon said. “For me, personally, it is important – on the weekend, I often use our services, and from the beginning.”

Indeed, the flexible, on-demand pricing is a very attractive proposition for independent researchers and developers who may only need a small computer for personal or university projects.

“People who are studying for a Masters or a PhD – that’s the category we want to stay in touch with because they’re usually people who are a few years away from doing something really great,” said Bryon.

Connect them now, and get rewards later when they hit the big time. That is the general context.

But there’s no escaping the big elephant in the room, one that all cloud companies must consider: the massive amount of power required to power this AI revolution.

A green machine

Part of DataCrunch’s “advantage” is that its data centers are located in the capital of Finland, Helsinki, and Iceland – a country that has been using 100% renewable energy for years already.

“In Helsinki, we can subscribe to green energy from the grid,” Bryon said. “And right now, in one of our two data centers in Finland, waste heat is being captured to heat Helsinki itself. In Iceland, we have the advantage that the ambient air temperature is always low, while the energy mix in the grid is already 100% green. So Iceland is one of the greenest places in the world to do these kinds of operations.”

This will be the main focus of the company moving forward. While it plans to offer its services to any company around the world, it will remain focused on the Nordics and Iceland. “Maybe in the future we will look at Canada if we can find the right places, where we can get the same benefit in terms of the carbon footprint of our operations,” said Bryon.

It’s these “green” credentials that DataCrunch hopes will further differentiate it from other European competitors: companies like FlexAI in France, which just came out of the blue with $30 million in funding; and Nebius, which recently emerged from the ashes of Russian internet giant Yandex and recently became a public company again.

There’s a trade-off here, though: While low latency is often one of the biggest selling points for computing AI providers, DataCrunch won’t necessarily be in that bucket, meaning it’ll be better suited to a specific type of computer. work.

“Our strategy is that we will not be the lowest latency provider because of being in 100 locations around the world,” said Bryon. “We’re very focused on a computer that doesn’t have that strong need for latency. We can still have 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 currently in shared “co-locations,” but the company says it plans to start building its own data centers in 2025 — something that will require more capital.

“I want us to go public with this company, and we will need access to more capital to continue growing the company,” said Bryon.


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