Chris Campbell: Sr. Director – AI Solutions - AIaaS/GPUaaS, Facilities & Infrastructure - chris.campbell@wwt.com 

Don Molaro: Chief Technical Advisor - Don.Molaro@wwt.com 

Global Partner Support Team: Global_Partner_Support@wwt.com 

Jason Yorn: VP of Global Channel & Alliances - jyorn@vultr.com - (513)-659-8599 (c)

Duncan Ng: VP of Solutions Engineering - (415) 205-8677 (c)

James Taylor: Dir. of Global Strategic Channels - jtaylor@vultr.com - (925) 525-1475 

Partnership Established Date - 2025

Partner Fiscal Year dates - Fiscal year ending Dec 31 

Preferred Authorized Distributors - Arrow Electronics

WWT can submit a lead by emailing dealreg@vultr.com with any relevant information and commercial details. 

Vultr competes directly with hyperscale cloud providers such as AWS, Microsoft Azure, and Google Cloud Platform (GCP). While offering a similar global footprint with 32 data centers worldwide, Vultr differentiates itself by providing higher-performance infrastructure at a lower cost, making it an attractive alternative for enterprises seeking predictable pricing, fast deployment, and optimized performance for both CPU and AI workloads. Unlike hyperscalers, Vultr combines enterprise-grade reliability with simplicity and agility, appealing to organizations looking to scale AI, compute, and multi-region workloads efficiently.

Vultr's partnerships with NVIDIA and AMD are core to delivering high-performance, AI-ready infrastructure for enterprises. As an NVIDIA Preferred Cloud Partner, Vultr works closely with NVIDIA's product teams and was the first cloud provider globally to deploy NVIDIA B200 GPUs into production environments, enabling faster access to next-generation AI compute. Vultr provides broad access to NVIDIA's GPU portfolio, supporting high-performance AI training, inference, and serving workloads with predictable costs and global reach.

Vultr has also deployed AMD MI300, MI325, and MI355X GPUs at scale and leverages AMD EPYC™ CPUs across its global platform. In 2026, Vultr and AMD co-developed VX1™, an exclusive, highly optimized CPU platform that delivers up to 77% greater price-to-performance than hyperscaler ARM-based solutions, enabling enterprises to run demanding workloads efficiently and cost-effectively.

Beyond NVIDIA and AMD, Vultr collaborates with a broad ecosystem of partners, including Dell, Supermicro, Cisco, HP, NetApp, DDN, Vast, and Weka, supporting scalable, multi-region AI and data-intensive deployments across regulated and performance-sensitive industries. 

Vultr maintains infrastructure and engineering resources ready for consumer testing and POC. 

Vultr complements WWT's AI Proving Ground by delivering global, enterprise-grade cloud compute infrastructure that integrates seamlessly with AI Studio, Foundry, and Factory. This partnership uniquely enables WWT teams to offer custom-built AI infrastructure in the cloud as a service. On average, Vultr helps customers reduce cloud spend by 50–70%, freeing capital to invest in additional AI initiatives and services.

• Named as Emerging Visionary in the Gartner® Emerging Market Quadrant (eMQ) for Generative AI Specialized Cloud Infrastructure
• Listed as Major Player in IDC MarketScape Worldwide Public Cloud Infrastructure as a Service Vendor Assessment
• Awarded Best Cloud Infrastructure in The Cloud Awards 2025/26
• Listed in CRN's Cloud 100 and as part of their 2026/2026 20 Coolest Cloud Infrastructure Companies
• Dell Technologies 2024 Global Alliances AI Provider of the Year, Americas

Vultr's solution targets both enterprises and AI natives. Industries where secure, compliant, and high-performance infrastructure is essential for scaling AI in production, including Entertainment, Healthcare, FInance, Telco, Energy, Retail, and the Public Sector (SLED). These verticals commonly require multi-region AI inferencing, data residency, and predictable performance to support latency-sensitive and regulated workloads. By combining AI-optimized cloud infrastructure with enterprise-grade security and cost transparency, this offering enables organizations in these industries to move AI use cases from pilot to production while maintaining operational control and regulatory alignment.

The ideal large enterprise organization is transitioning AI workloads into production or is already production-ready. These customers are running or planning AI inferencing workloads that require predictable performance, low latency, and strong cost control across distributed environments. 

Buying decisions are typically driven by senior technology leaders (including the CTO, CIO, VP of AI, and AI COE Leads) who are accountable for scaling AI initiatives while managing cloud spend, security, and compliance. This offering supports organizations operating across multiple geographies with requirements for data residency, regulatory compliance, and greater infrastructure control beyond traditional hyperscalers.