ScaleOps secures $130 million funding to boost compute efficiency for AI workloads

The AI boom is in full swing, yet companies are hemorrhaging money on wasted compute power. Expensive GPUs sit idle, workloads are overprovisioned, and cloud bills keep rising. ScaleOps argues the core issue isn't a hardware shortage—it's inefficient resource management.

The startup, which develops software to automatically manage and reallocate computing resources in real time, announced a $130 million Series C funding round on Monday, valuing the company at $800 million. Insight Partners led the round, with participation from existing investors Lightspeed Venture Partners, NFX, Glilot Capital Partners, and Picture Capital. ScaleOps claims its platform can slash cloud and AI infrastructure costs by up to 80%.

Co-founded in 2022 by former Run:ai engineer Yodar Shafrir, ScaleOps was born from witnessing the struggles companies face managing complex AI workloads. While tools like Kubernetes help orchestrate applications across large machine clusters, their reliance on static configurations often fails to adapt to rapid demand changes. This results in underutilized GPUs, performance bottlenecks, and significant financial waste.

"In my previous role at Run:ai, I spoke with many customers, particularly DevOps teams," Shafrir, now CEO of ScaleOps, told TechCrunch. "They appreciated what Run:ai offered but still grappled with managing production workloads, especially with the rise of AI inference. Looking at the bigger picture, I saw the problem wasn't confined to GPUs. It encompassed compute, memory, storage, and networking. The same pattern of inefficient resource management kept recurring."

DevOps teams often spent excessive time coordinating with multiple stakeholders to fix issues, with limited success. While many tools could identify problems, they rarely provided automated solutions. This gap presented a clear market opportunity.

ScaleOps aims to bridge that gap by dynamically aligning application requirements with infrastructure decisions, offering a fully autonomous, end-to-end management solution, Shafrir explained.

"Kubernetes is a powerful, flexible, and highly configurable system. But that configurability is also its weakness," Shafrir noted. "It depends on static settings, while modern applications are dynamic. This mismatch creates constant manual toil across teams. What's needed is a system that understands each application's unique context—its needs, behavior, and the evolving environment."

image credits: Scaleops

The market includes competitors like Cast AI, Kubecost, and Spot. According to Shafrir, while many offer automation, their solutions often lack full context, risking performance degradation or downtime and eroding trust among teams managing production systems.

ScaleOps says its platform was designed from inception for production environments. It is fully autonomous, context-aware, and requires no manual setup—features the company believes set it apart.

Headquartered in New York, ScaleOps serves enterprise customers worldwide, particularly those using Kubernetes. Its client base includes large organizations and companies across Europe and India, such as Adobe, Wiz, DocuSign, Salesforce, and Coupa.

This Series C round follows a $58 million Series B in November 2024. Shafrir stated that demand for autonomous cloud infrastructure management has surged, and the company is still in its early growth phase. A spokesperson confirmed total funding now stands at approximately $210 million.

ScaleOps reported over 450% year-over-year revenue growth and a tripling of its workforce in the past year, with plans to more than triple headcount again by the end of the current year.

The new capital will fuel product development and platform expansion. As AI accelerates compute demand, efficient infrastructure management becomes paramount. The startup is committed to advancing its vision of fully autonomous infrastructure.