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At full deployment, 30 MW of dedicated AMD compute across Rackspace's footprint will represent meaningful capacity to serve regulated enterprise workloads, including healthcare providers who have expressed early interest in accelerated compute for clinical AI and inference at scale. This collaboration incorporates both AMD Instinct GPUs (including MI355X, MI350P, and future successor solutions) and AMD EPYC CPUs inside an integrated Enterprise AI Cloud architecture, enabling Rackspace to route each workload to the right compute with full accountability for performance and outcomes end to end.
"Enterprises in regulated industries need AI infrastructure that is governed from the ground up, with one operator accountable for business outcomes, not a collection of vendors each owning a piece," said Gajen Kandiah, CEO, Rackspace Technology. "This collaboration combines the right compute with the right operating model and delivers something the market hasn't offered before: a governed AI stack with one accountable partner from silicon to outcomes."
"As enterprise AI evolves, customers need infrastructure that can deliver the right mix of accelerated and general-purpose compute for each workload," said Dan McNamara, senior vice president and general manager, Compute and Enterprise AI, AMD. "By bringing together leadership AMD AI compute solutions and Rackspace's governed cloud operating model, we are helping regulated enterprises deploy high-performance AI infrastructure with the openness, scalability and accountability needed to run AI at enterprise scale."
Both companies expect to dedicate sales and marketing resources to identify and engage enterprise customers for AMD compute-powered infrastructure, with each company committing personnel to jointly develop and pursue customer opportunities across regulated industries.
This agreement will accelerate delivery of the four integrated capabilities announced with the MOU: Enterprise AI Cloud, Enterprise Inference Engine, Inference as a Service, and Bare Metal AMD Instinct, offering a complete, governed stack from bare metal compute through fully operated inference. Together, the companies aim to establish a new category of managed enterprise AI infrastructure that offers enterprises an alternative to the bare metal model. The shift from AI experiments to agentic workflows running inside core enterprise systems is accelerating demand for exactly the kind of governed, accountable infrastructure this collaboration is built to deliver.
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