Verda Secures $189M Series B to Scale AI Cloud Infrastructure Across Europe and Beyond

Verda Achieves Unicorn Status with $189M Series B Funding Round

Verda, the Helsinki-based AI cloud company formerly known as DataCrunch, has secured $189 million in a Series B funding round led by Emergence Capital, catapulting the firm to unicorn status with a valuation exceeding $1 billion1

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. The oversubscribed round attracted significant participation from MUFG Innovation Partners, Supermicro, Varma Mutual Pension Insurance Company, Lifeline Ventures, 6 Degrees Capital, byFounders, and Finnish state investor Tesi1

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. Angel investors including Ola Tørudbakken, Director of AI Systems at Meta, and Mark Saroufim, cofounder of Core Automation, also joined the round2

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. This latest injection brings the company's total capital raised to more than $450 million across equity and debt2

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Rapid Revenue Growth Signals Strong Market Demand for AI Infrastructure

The European neocloud provider has demonstrated remarkable growth momentum, with its annualized revenue run rate reaching $165 million in July, a substantial leap from the $60 million figure reported during its April funding round just months earlier1

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. Joe Floyd, general partner at Emergence Capital, emphasized that "demand for AI compute is insatiable, and the gap between demand and supply is growing"1

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. Founded in 2020, Verda has positioned itself uniquely by managing the entire stack—from physical data centers and hardware to its cloud platform and AI research capabilities1

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. The company currently powers AI workloads for organizations across more than 50 countries, serving clients from early-stage startups to large enterprises2

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Aggressive Expansion Plans Target Global AI Infrastructure Market

Verda plans to deploy the fresh capital toward expanding computing capacity severalfold within a year, with a focus on inference optimization and platform development1

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. The company aims to operate more than 250 megawatts in 2027, with data center capacity already live in Finland and additional facilities coming online across Europe, the United Kingdom, the United States, and Asia2

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. Verda has already established offices in London and San Francisco in recent months and intends to expand further across these regions1

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. The company is preparing early deployments of Nvidia VR200 NVL72 rack-scale supercomputers in the coming months2

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Verda Differentiates Through AI Inference for Enterprises and Internal Research

The company provides large-scale managed AI inference to enterprise-level companies with high optimization and reliability, building its own compilers and serving software while providing performance and reliability engineering2

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. Verda's internal AI lab runs real research workloads on the platform, tackling engineering challenges such as improving GPU utilization, inference optimization, and kernel engineering2

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. Notable clients include sovereign AI development firm Aleph Alpha, which uses Verda for its research and development infrastructure, and Magnific, which relies on Verda for AI inference for media generation at millions of requests per day2

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. Epsilon Health trains bespoke radiology AI model training on a dedicated Verda cluster using native image resolution2

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. Arjun Karpur, Head of Machine Learning at Epsilon Health, noted: "What we didn't expect was a team of engineers who could help us design our own data streaming and cluster management, not just hand us a cluster and walk away"2

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Strategic Focus on Reducing Carbon Footprint and Evolving AI Workloads

Founder and CEO Ruben Byron articulated the company's ambitious vision: "AI is becoming critical infrastructure across industries, and the next few years are a pivotal window for Europe. Our north star is to build the first true tech company in Europe, with AI infrastructure as the starting foundation, and to bring down the carbon footprint of compute worldwide"1

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. Byron also emphasized the urgency: "There's a window right now to build one of the defining compute companies of this generation, and to do so from Europe. It won't be open for long"2

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. The company recognizes that today's AI workloads differ significantly from those of previous years, featuring longer sessions, context accumulation over many turns, and agentic use cases2

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. To address these evolving demands, Verda is investing in faster provisioning and setup times for instant clusters while strengthening co-research partnerships with AI labs, open-source projects, and developer tool companies to understand emerging model architectures and optimization techniques2

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. The company plans to enhance developer experience by shipping new features that build enterprise trust and strengthen platform robustness2

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