The agreement highlights rising demand for high-performance, compliant infrastructure as AI workloads scale into regulated environments
Corvex, Inc., (MOVE) an AI cloud computing company focused on GPU-accelerated infrastructure, announced a long-term GPU lease agreement with an established AI-driven provider of high-performance battery technologies. The deployment will consist of a dedicated cluster of NVIDIA H200 GPUs designed to support the customer’s core AI research and development initiatives, including proprietary algorithm development.
The customer selected Corvex based on its strong overall value proposition, confidential AI enablement capabilities, and hyperscaler-class operational standards compared with other AI cloud infrastructure providers. Corvex’s GPU cluster architecture is designed to maximize compute density while maintaining elasticity, giving customers the ability to scale efficiently and access burst capacity during periods of peak demand. This approach aims to improve price-to-performance while reducing idle resources—an increasingly critical factor as AI training and inference workloads grow more compute intensive.
Beyond cloud deployment, Corvex is also enabling the customer to expand into the most security-conscious enterprise environments through a secure, managed on-premise solution. By building next-generation on-premise GPU clusters with hardware-enforced encryption, remote attestation, and payload-free telemetry, Corvex allows sensitive model training and production inference to run while meeting strict requirements around data sovereignty, compliance, and IP protection. This capability opens the door to serving enterprises that cannot use public cloud infrastructure due to regulatory or internal governance constraints.
Corvex is also providing a fully managed Kubernetes service intended to deliver hyperscaler-grade orchestration without the cost or lock-in typically associated with hyperscalers. The platform automates scheduling to maximize GPU utilization, minimize idle capacity, and reduce infrastructure overhead, allowing engineering teams to focus on AI model development instead of infrastructure management.
Corvex Co-CEO Jay Crystal said the deployment demonstrates how AI innovators can scale production workloads without sacrificing economics or operational velocity. Co-CEO Seth Demsey added that the deal reflects growing demand for secure, easy-to-use GPU infrastructure that is more cost-effective than legacy offerings, positioning Corvex as a platform for enterprise-grade AI at scale.
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