Vultr and Digital Realty have announced a partnership designed to make enterprise-ready AI infrastructure easier to access across global markets. The
collaboration integrates Digital Realty’s extensive data center platform with Vultr’s GPU-accelerated cloud to give businesses direct, low-latency access to the computing power needed for AI workloads.
Sovereign-Ready AI Infrastructure
AI adoption is accelerating, but enterprises still face hurdles around performance, compliance, and data proximity. Running workloads in the wrong location can create bottlenecks, drive up costs, and complicate regulatory requirements. Digital Realty and Vultr are addressing these challenges by aligning infrastructure with where data resides and making high-density GPU resources available on demand.
Kevin Cochrane, CMO at Vultr, emphasized the compliance dimension to ChannelE2E. He said, “Vultr enables sovereign cloud options for all customers across our 32 global data centers, giving enterprises the ability to keep their most critical data in-region while still accessing GPU-accelerated AI, cloud compute, and bare metal infrastructure. From a risk management perspective, we recommend that customers who place the highest value on data sovereignty and compliance deploy AI workloads - training, inference, or general cloud compute - within Vultr’s sovereign-ready regions. This ensures data residency, reduces exposure to regulatory risks, and provides the performance and flexibility enterprises need without reliance on hyperscale centralization.”
Vultr’s GPU clusters, powered by NVIDIA HGX B200 and AMD Instinct MI325X chips, are now deployed on
Digital Realty’s PlatformDIGITAL. Enterprises connect to these resources through ServiceFabric, which provides direct interconnection and access to the AI Private Exchange (AIPx). This setup allows organizations to move AI workloads into pre-validated environments for training, inference, and agent-based systems without the burden of building their own custom infrastructure.
Partners at the Center of Enterprise AI Delivery
Cochrane explained how partners fit into this equation. For MSPs and channel partners, demand for AI services from mid-market enterprises is rising quickly, but delivering those services often requires access to advanced hardware, global reach, and compliant architectures. That is where this partnership opens the door.
"Vultr makes it easy for MSPs and channel partners to deliver AI services by giving access to top-tier NVIDIA and AMD GPUs, along with cloud compute and bare metal in 32 global locations. Through the Vultr Cloud Alliance, and with partners like Digital Realty, Megaport, Console Connect, DDN, NetApp and others, we provide the connectivity, storage, and performance needed for training and large-scale deployments. For inference, we extend this with expertise and partnerships across the ecosystem, ensuring optimized pipelines that meet industry-specific compliance and performance requirements. Together, Vultr and Digital Realty give partners the tools to deliver compliant, high-performance AI, from training to inference for the mid-market," explained
Cochrane.
By positioning partners at the center of the deployment model, Vultr and Digital Realty are expanding the reach of enterprise AI infrastructure beyond the largest corporations. This approach enables MSPs and channel providers to deliver advanced AI capabilities to customers who may not have the resources to build or manage these environments themselves, while still meeting the compliance and performance thresholds expected in regulated industries.
The Enterprise Impact
For enterprises, the advantages are clear. Workloads can be deployed immediately in environments designed for AI performance. Capacity scales with demand, avoiding the friction of long-term commitments. Localized infrastructure supports compliance and sovereignty requirements in different regions. The architecture itself has been built with AI in mind, optimized for high-density GPU computing rather than retrofitted from legacy systems.
That flexibility extends to hardware choice as well. “Since AI is still relatively new and standards are not yet defined, different AI workloads require different GPU types and performance levels,” Cochrane noted. “Vultr works with customers across industries such as healthcare, financial services, media, gaming, and the public sector to align training, fine-tuning, and inference with the right NVIDIA or AMD GPUs, cloud compute, or bare metal. This ensures the infrastructure fits into their existing stack while balancing compliance, performance, and cost efficiency, and helps them make informed decisions that work not only for proof of concept but for long-term production.”
This partnership represents a shift in how AI infrastructure is delivered. Instead of focusing solely on raw performance, the emphasis is on accessibility, compliance, and production readiness. It is enabling organizations to scale AI in ways that align with cost, regulatory, and operational realities. The result is AI infrastructure that sits closer to the data and removes much of the complexity that has slowed enterprise adoption.
