The AI revolution is consuming enormous amounts of computing power, but a staggering portion of it is being wasted. GPUs sit idle, workloads are over-provisioned, and cloud bills keep climbing. ScaleOps, a startup that builds software to automatically manage and reallocate computing resources in real time, believes the real problem is not a shortage of compute — it is mismanagement.
The company announced Monday that it has raised $130 million in a Series C round at an $800 million valuation. The round was led by Insight Partners, with participation from existing backers Lightspeed Venture Partners, NFX, Glilot Capital Partners, and Picture Capital. ScaleOps claims its software can reduce cloud and AI infrastructure costs by as much as 80%.
The funding comes roughly a year and a half after ScaleOps raised $58 million in its Series B in November 2024. The company's total funding now stands at approximately $210 million.
Born From Frustration
ScaleOps was co-founded in 2022 by Yodar Shafrir, a former engineer at Run:ai, the GPU orchestration startup that was later acquired by Nvidia. During his time there, Shafrir witnessed firsthand how companies struggled to manage increasingly complex AI workloads.
Shafrir told TechCrunch that while working at Run:ai, he met many customers — especially DevOps teams — who were having difficulty managing production workloads, particularly as inference became more common. When he looked at the bigger picture, he realized the problem went beyond GPUs. It extended across compute, memory, storage, and networking, with the same inefficiency patterns repeating everywhere.
The existing tools on the market offered visibility into these problems but stopped short of delivering actual fixes. That gap between diagnosis and solution revealed a significant market opportunity — and ScaleOps was built to fill it.
The Kubernetes Problem
At the core of ScaleOps' value proposition is a fundamental limitation in Kubernetes, the widely used system for running applications across large clusters of machines. While Kubernetes is flexible and highly configurable, it relies heavily on static configurations that struggle to keep pace with fast-changing demand, leading to underused GPUs, performance issues, and costly inefficiencies.
Shafrir explained that modern applications are highly dynamic, but Kubernetes still requires constant manual work across teams to keep things running smoothly. What is needed, he said, is a system that understands each application's context — what it requires, how it behaves, and how the surrounding environment is shifting.
ScaleOps addresses this by connecting application needs with infrastructure decisions in real time, providing what the company describes as a fully autonomous, end-to-end management solution.
Standing Out in a Crowded Market
ScaleOps is not the only company tackling cloud cost optimization. Competitors include Cast AI, Kubecost (acquired by IBM), and Spot (acquired by NetApp). However, Shafrir argues that many automation tools in the market operate without full context, which can lead to performance issues and even downtime — limiting trust among teams running critical production environments.
ScaleOps says its platform was built specifically for production environments from the ground up. It is fully autonomous, context-aware, and works out of the box without requiring manual configuration — capabilities the company believes set it apart.
Enterprise Traction and Rapid Growth
The startup is already serving major enterprise customers globally. Its client roster includes Adobe, Wiz, DocuSign, Salesforce, and Coupa, with a footprint that spans large organizations across Europe and India.
The growth numbers back up the momentum. ScaleOps reports more than 450% year-over-year growth and has tripled its headcount over the past 12 months, with plans to more than triple it again by year-end.
What's Next
With the new capital, ScaleOps plans to launch new products and expand its platform as AI continues to drive compute demand. The company says it will keep building toward fully autonomous infrastructure management — a vision that becomes more urgent as enterprises pour billions into AI but struggle to use those resources efficiently.
In an era where every GPU cycle counts and cloud costs can make or break an AI strategy, ScaleOps is betting that the companies that manage compute best will be the ones that win.
