Verda Raises $189M in Funding
Verda, the full-stack AI cloud of tomorrow, led by Ruben Bryon and the team, has raised $189 million in new funding. The oversubscribed Series B was led by Emergence Capital, with MUFG Innovation Partners, Supermicro, Varma Mutual Pension Insurance Company, Lifeline Ventures, 6 Degrees Capital (6DC), byFounders, Tesi (Finnish Industry Investment Ltd), and a group of angel investors including Ola Tørudbakken and Mark Saroufim participating. That brings the total funding to date to over $450 million across equity and debt.
"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." — Ruben Bryon, founder and CEO
Building the AI Cloud of Tomorrow.
For years, access to compute capacity was primarily a procurement problem. Teams negotiated for months, took delivery of fixed infrastructure, and structured workloads around whatever capacity had been allocated. That model worked when capacity was scarce, and workloads were relatively predictable.
AI has changed that equation. Training runs increasingly need infrastructure that is already available, while production inference requires capacity that can scale with strict latency and availability requirements. Agentic workloads add another layer of complexity, with context accumulating across interactions and demand arriving in unpredictable bursts, often spiking as soon as a tool call returns. As a result, decisions around how much capacity is needed and when are increasingly being made by engineering teams rather than annual procurement cycles.
Verda is building an integrated AI cloud stack spanning data centers, the infrastructure within them, and the platform that runs on top. The approach is designed to provide compute capacity when, where, and how customers need it, while operating at a lower carbon footprint than the industry average.
The latest funding strengthens all three layers, supporting additional data center capacity alongside deeper investment in the platform, AI Lab, and capabilities already being used by customers.
Teams Already Run Their Production AI on Verda.
Verda now powers AI workloads for organizations across more than 50 countries, ranging from early-stage startups to large enterprises. The company reached a $165 million annualized revenue run rate in July 2026 and has grown to more than 250 employees across Helsinki, London, Taipei, and San Francisco.
Verda’s GPU clusters support Aleph Alpha’s R&D infrastructure, with engineers-in-residence collaborating on the underlying software stack. Magnific handles media-generation workloads at millions of requests per day on Verda’s infrastructure. Epsilon Health trains its radiology AI models on a dedicated Verda cluster, enabling training at native image resolution.
AI Lab Lives on the Platform Customers Use.
Verda builds its own compilers and serving software, alongside dedicated performance and reliability engineering. Its AI Lab runs real research workloads directly on the same platform used by customers, tackling complex engineering challenges such as GPU utilization, inference optimization, and kernel engineering.
This work helps customers extract more performance from their infrastructure while directly shaping Verda’s product roadmap. By operating at the frontier of real-world AI workloads, the Lab can identify infrastructure gaps and develop solutions before they become customer requirements.
"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." - Arjun Karpur, Head of Machine Learning, Epsilon Health
What’s Next.
More capacity: Verda is targeting more than 250 MW of operational capacity in 2027, with data centers already live in Finland and expansion underway across Europe, the UK, US, and Asia. Early deployments of NVIDIA VR200 NVL72 are also expected in the coming months.
Inference at scale: Longer sessions, accumulating context, and agentic workloads are creating more dynamic demand. Verda is investing in infrastructure and model access designed to serve thousands of concurrent inference workloads efficiently.
Faster provisioning: Faster instance and cluster spin-up, storage attachment, and infrastructure response times are being developed to reduce deployment bottlenecks.
Platform expansion: Following Container Registry, S3-compatible Object Storage and Managed Kubernetes are planned additions, while Instant Clusters now support pre-configured Kubernetes with Kueue or Slurm via Slinky.
Enterprise readiness: New capabilities include Audit Logs, SSO for IAM, expanded Confidential Computing with NVIDIA HGX B300 and B200 support, and SOC 2 Type II and C5 certifications.
Engineering & developer experience: The AI Lab is deepening collaboration with research teams, open-source projects, developer-tool companies, and customers, with those insights informing hardware, infrastructure, and software decisions. The platform continues to support developers through the console, CLI, and APIs.
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