Artificial intelligence may be booming, but behind the scenes, companies are wasting vast amounts of expensive computing. GPUs sit idle, workloads are excessive, and cloud costs continue to rise. ScaleOps believes the problem isn’t scarcity – it’s mismanagement.
The startup, which makes 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 cuts cloud and AI infrastructure costs by up to 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 on large clusters of machines, they often rely on static configurations that struggle to keep up with rapidly changing demand, leading to GPU underutilization, performance issues, and costly inefficiencies.
“As part of my role [at Run:ai]I met a lot of customers, especially DevOps teams,” Shafrir, who is the company’s CEO, told TechCrunch. 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 themselves. teams failed to manage resources effectively.”
DevOps teams often found themselves chasing multiple stakeholders to solve problems, and all too often these efforts failed. Most existing tools offered visibility into problems but did not provide real solutions. This gap revealed a significant market opportunity.
ScaleOps connects application needs with real-time infrastructure decisions 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 the problem,” Shafrir said. “Kubernetes relies heavily on static configurations. Applications today are highly dynamic, which requires constant manual work in teams. You need something that understands the context of each application—what it needs, how it behaves, and how the environment changes.”
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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 a full framework, which can lead to performance issues and even outages, reducing trust between teams running production environments, according to the CEO.
The startup says its platform was built specifically for production from the ground up. It’s fully autonomous, context-aware, and works seamlessly without requiring manual configuration — features the company believes differentiate ScaleOps from competitors.
The New York-based company serves enterprise customers worldwide, particularly those running Kubernetes-based infrastructures, with a footprint spanning large organizations as well as companies across Europe and India. ScaleOps says its platform is used by a number of enterprise customers, including Adobe, Wiz, DocuSign, Salesforce and Coupa.
The Series C funding comes about a year and a half after ScaleOps raised $58 million in a Series B round in November 2024. Since then, the group has seen strong demand for standalone cloud infrastructure management solutions, Shafrir said, adding that it is still in the early stages of development. The company’s total funding is about $210 million, according to a spokesperson.
ScaleOps said it has seen growth of more than 450% year-on-year and has tripled its headcount in the past 12 months, with plans to more than triple again by the end of the year.
With the new capital, ScaleOps plans to launch new products and expand its platform. As artificial intelligence drives demand for computing, managing this infrastructure becomes increasingly critical. The startup said it will continue to build toward fully autonomous infrastructure.
