AI inferencing and agentic applications are driving new enterprise use cases, with deployments spanning on-premises, neoclouds, and public clouds.
The platform now supports a broad range of workloads, including traditional virtualization, Kubernetes, and AI applications.
Security, governance, and cost management are key differentiators for enterprise AI adoption.
Early AI use cases include document search, compliance monitoring, and financial fraud investigation, primarily on-premises.
The company expects to benefit from the AI inferencing wave by providing a flexible, multi-location platform.
Significant customer migration is occurring from VMware, with 700–1,000 new customers added per quarter, mostly from VMware.
Main competitors include IBM Red Hat and public cloud providers, but the platform is positioned as a hybrid leader with high customer satisfaction.
The platform enables in-place migrations, allowing customers to retain existing hardware and storage, reducing migration complexity.
Automated migration tools streamline the process, minimizing data movement and downtime.
The company’s hybrid approach contrasts with competitors focused solely on public or private cloud.
Subscription-based business model and renewals provide improved revenue visibility compared to prior years.
Supply chain challenges, especially server availability and pricing, are impacting revenue recognition timing.
External storage and public cloud support help mitigate hardware constraints, expected to grow through 2027 and beyond.
Land and expand business is closely tied to server core count, with higher core counts driving expansion.
Customers are seeking pricing certainty and longer contract durations, with recent deals averaging 3.4 years.
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