ScaleOps Launches AI Infrastructure Resource Management Product to Power Self-Hosted AI at Scale

ScaleOps expands its cloud resource management platform to self-hosted GenAI models and GPU-based applications, enabling enterprises to run AI at scale with optimal performance and zero waste.

NEW YORK, Nov. 20, 2025 /PRNewswire/ -- ScaleOps, the market leader in cloud resource management, today announced the launch of its AI Infra Product, expanding its proven capabilities to manage resources for self-hosted AI models and GPU-based applications at scale, redefining how enterprises manage and optimize AI infrastructure.

The ScaleOps platform automatically manages production environments in real time for industry leaders, including Wiz, DocuSign, Rubrik, and Coupa, Alkami, Vantor, Grubhub, Island, Chewy, and Fortune 500 Companies. With the AI Infra Product launch, ScaleOps extends its capabilities to help AIOps and DevOps teams run self-hosted LLM and AI models, enabling organizations to improve GPU efficiency, eliminate waste, and scale their AI workloads efficiently.

As companies increasingly deploy self-hosted AI models at scale, engineering teams face major challenges. Wasted GPU costs are a major pain point - companies often fail to fully utilize their GPUs, resulting in low utilization and substantial wasted cloud spend.^[1] Performance issues worsen the problem - large models cause long load times and latency during demand spikes, prompting teams to overprovision GPUs and incur higher costs. Engineers waste valuable time on manual tuning, constantly adjusting workloads to maintain performance.

The ScaleOps AI Infra Product provides a complete resource management solution for self-hosted GenAI models and GPU-based applications in cloud native environments. It intelligently allocates and scales GPU resources in real-time, increases utilization, accelerates model load times, and continuously adapts to dynamic demand. By combining application context-awareness with real-time continuous automation, ScaleOps keeps self-hosted AI models running optimally, eliminating GPU waste, driving substantial cost savings, and freeing engineering teams from repeated manual tuning.

"Cloud-native AI infrastructure is reaching a breaking point," said Yodar Shafrir, CEO and Co-Founder of ScaleOps. "Cloud-native architectures unlocked great flexibility and control, but they also introduced a new level of complexity. Managing GPU resources at scale has become chaotic - waste, performance issues, and skyrocketing costs are now the norm. The ScaleOps platform was built to fix this. It delivers the complete solution for managing and optimizing GPU resources in cloud-native environments, enabling enterprises to run LLMs and AI applications efficiently, cost-effectively, and while improving performance."

Already deployed in customers' production environments, the ScaleOps AI Infra Product has driven savings of 50-70%, with large enterprises projecting tens of millions of dollars in annual savings as they modernize their GPU operations.

"ScaleOps provides enterprises with a complete, holistic solution that brings together every aspect of cloud resource management - enabling them to manage all their cloud workloads at scale." said Shafrir.

To learn more about the AI Infra Product and how ScaleOps powers the AI factory, visit scaleops.com/ai

^[1]  Forrester, AI Cost Optimization: The Why, What, and How

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SOURCE ScaleOps