AI may be booming, but behind the scenes, companies are wasting vast amounts of expensive compute. GPUs sit idle, workloads are over-provisioned, and cloud costs continue to climb. ScaleOps believes the problem isn’t a shortage — it’s mismanagement.
The startup, which builds software that automatically manages and reallocates computing resources in real-time, has raised $130 million at an $800 million valuation, ScaleOps said Monday. The Series C funding round was led by Insight Partners, with participation from existing investors, including Lightspeed Venture Partners, NFX, Glilot Capital Partners, and Picture Capital. The company says its software reduces cloud and AI infrastructure costs by as much as 80%.
ScaleOps was co-founded in 2022 by Yodar Shafrir, a former engineer at Run:ai, a GPU orchestration startup acquired by Nvidia, after seeing firsthand how difficult it was for companies to manage increasingly complex AI workloads. While tools like Kubernetes help run applications across large clusters of machines, they often rely on static configurations that struggle to keep up with fast-changing demand, leading to underused GPUs, performance issues, and costly inefficiencies.
“As part of my role [at Run:ai], I met many customers, especially DevOps teams,” Shafrir, who is the company’s CEO, told TechCrunch. “While they really liked what Run:ai provided, they still struggled to manage their production workloads, especially as inference workloads became more common in the AI era. When I zoomed out, I realized the problem wasn’t just GPUs. It extended to compute, memory, storage, and networking. The same patterns kept repeating; teams were failing to manage resources efficiently.”
DevOps teams often found themselves chasing down multiple stakeholders to resolve issues, and too often, those efforts fell short. Most existing tools offered visibility into problems, but stopped short of delivering actual solutions. That gap revealed a significant market opportunity.
ScaleOps connects application needs with infrastructure decisions in real time and provides a fully autonomous solution that manages infrastructure end-to-end, Shafrir said.
“Kubernetes is a great system. It’s flexible and highly configurable. But that’s also the problem,” Shafrir said. “Kubernetes relies heavily on static configurations. Applications today are highly dynamic, which requires constant manual work across teams. You need something that understands the context of each application—what it needs, how it behaves, and how the environment is changing.”
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There are several players in this space, including Cast AI, Kubecost and Spot. While many companies have introduced automation tools, they often operate without full context, which can lead to performance issues and even downtime, limiting trust among teams running production environments, according to the CEO.
The startup says its platform was built specifically for production from the ground up. It is fully autonomous, context-aware, and works out of the box without requiring manual configuration — capabilities the company believes differentiate ScaleOps from competitors.
The New York-headquartered company serves enterprise customers globally, particularly those operating Kubernetes-based infrastructure, with a footprint that spans large organizations as well as companies across Europe and India. ScaleOps says its platform is used by a range of enterprise clients, including Adobe, Wiz, DocuSign, Salesforce and Coupa.
The Series C funding comes roughly a year and a half after ScaleOps raised $58 million in its Series B round in November 2024. Since then, the team has seen strong demand for autonomous solutions to manage cloud infrastructure, Shafrir said, adding that it is still in the early stages of its growth. The company’s total funding is about $210 million, according to a spokesperson.
ScaleOps said it has seen more than 450% year-over-year growth and that it has tripled its headcount over the past 12 months, with plans to more than triple it again by year-end.
With the new capital, ScaleOps plans to roll out new products and expand its platform. As AI drives demand for compute, managing that infrastructure is becoming increasingly critical. The startup said it will continue building toward fully autonomous infrastructure.
