VAST Data, the AI Operating System company, announced an expanded collaboration with AMD to help AI cloud providers and enterprises build and operate high-performance AI factories at scale. The collaboration brings together the VAST AI Operating System with 6th Gen AMD EPYC™ CPUs and AMD Instinct™ GPUs to support scalable training, inference and agentic AI workloads with improved efficiency, flexibility and performance.
As organizations move beyond model training and begin operationalizing AI agents, reasoning systems, and large-scale inference services, infrastructure requirements are rapidly changing. Success is increasingly determined not only by compute performance, but by how efficiently organizations can manage data, memory, context and compute resources as a unified system.
Crucial to this unified approach is VAST’s inherently versatile Disaggregated Shared Everything (DASE) architecture, which extends beyond standard storage to deliver robust multi-tenancy support for secure workload isolation, native multi-protocol access, and a unified global namespace that simplifies data access across distributed environments. By streamlining critical data operations like rapid model loading alongside VAST’s core data platform values, the system allows AI clouds to run massive, concurrent workloads while maximizing hardware utilization.
Many of today’s AI environments were designed for training-centric workflows yet struggle to support the expanding persistent context of retrieval augmented generation (RAG) pipelines and long-thinking, multi-turn inferencing. As a result, many organizations face rising infrastructure and token costs, underutilized GPUs and increasing operational complexity as they scale AI into real-world applications.
Also Read: Advantech Unveils Next-Gen AI Infrastructure Solutions Powered by AMD EPYC™ 9006 Series Processors
To address these challenges, VAST and AMD are expanding their collaboration to deliver an open and flexible approach to AI infrastructure that combines accelerated computing, intelligent data services and optimized inference software into a unified platform for AI clouds and enterprise AI deployments.
“AI is entering an operational phase where infrastructure efficiency matters as much as model performance,” said John Mao, Vice President, Global Technology Alliances at VAST Data. “The industry is discovering that inference is fundamentally a data problem. Success depends on how effectively organizations can bring data, compute, memory and intelligence together as a single system. The VAST AI Operating System was built for this transition, giving AI cloud providers and enterprises a more efficient, scalable and open foundation for training, inference and the next generation of agentic AI applications.”
“The future of AI will be built on an open ecosystem that gives organizations the flexibility to choose the technologies that best meet their performance, operational and business requirements,” said Derek Dicker, Corporate Vice President, Enterprise Business Group at AMD. “Our expanded collaboration with VAST combines AMD EPYC CPUs and Instinct GPUs with the software foundation customers need to accelerate inference, improve infrastructure efficiency and deploy AI at scale. Together, we’re enabling AI clouds and enterprises to build high-performance AI factories without compromise.”
Growing Momentum Across the AI Ecosystem
Leading AI clouds are embracing VAST because AI infrastructure is evolving beyond GPU rental and training workloads. As providers build platforms for large-scale inference and agentic AI, they need architectures that combine accelerated computing, data infrastructure and context management into a unified system – delivering performance, flexibility and operational simplicity at scale.
“As AI moves into production, customers need infrastructure that can securely and reliably support increasingly complex workloads without sacrificing performance,” said Raghu Chakravarthi, EVP of Engineering and General Manager – Americas at Core42. “Our infrastructure strategy is built on a silicon agnostic approach to give customers the best optionality and output for their use cases. The combination of AMD accelerated computing and the VAST AI Operating System provides a powerful foundation for delivering enterprise-grade AI services across sovereign and commercial environments with the scale, efficiency and operational simplicity our customers expect.”
“Every frontier lab, every AI-native company building the future of AI needs infrastructure that scales as fast as their ambitions,” said Erwan Menard, SVP Product Management at Crusoe. “Our collaboration with AMD and VAST gives Crusoe Cloud customers a validated foundation purpose-built for AI – combining accelerated compute performance with the data and storage scalability that training and inference workloads demand, so they can spend less time integrating infrastructure and more time building their future.”
“Organizations want the freedom to build AI on the infrastructure that best fits their needs,” said Kevin Cochrane, CMO at Vultr. “The collaboration between AMD and VAST gives customers more flexibility in how and where they deploy AI, as well as the scale and performance required for enterprise workloads.
That’s exactly the kind of flexibility customers are looking for as they scale AI across diverse environments.”
“Many organizations understand the potential of AI but are still working through the operational realities of deploying it at scale,” said David Bitton, Vice President, AI and Product Strategy at 5C. “Validated architectures developed by AMD and VAST help reduce complexity, accelerate deployment and give customers greater confidence as they move from pilots to production AI environments.”
“The AI market is increasingly looking for high-performance alternatives that provide both scalability and flexibility,” said Piotr Tomasik, President & COO and Co-Founder at TensorWave. “As an AMD-centric AI cloud, we’ve seen firsthand how rapidly the ecosystem has evolved. Collaborations like this help accelerate adoption by giving customers a validated architecture that combines modern AI infrastructure software with AMD accelerated computing.”
“Agentic AI moves the inference bottleneck beyond raw compute to context: long-running, multi-turn agents make cache, state, and data movement part of the performance path itself,” said Pin Siang Tan, CTO, Embedded LLM. “Embedded LLM works with AI clouds and enterprises to turn AMD accelerator capacity into production AI services, and we’re collaborating with VAST to make its data platform the persistent foundation of that work, from KV-cache reuse today to agent state, replay, and reinforcement-learning data ahead.”
“One of the biggest challenges in large-scale AI is efficiently managing large and concurrent context windows as agents retrieve, reason over, and generate information across massive datasets,” said Dhanaseker Kandhasamy, Co-Founder at Phanos.AI. “At Phanos.AI, we leverage VAST and AMD capabilities including purpose-built storage, compute, network, and software-stack observability to drive real-time decision-making on workload placement for optimal performance. The innovations AMD and VAST are bringing to inference infrastructure help address a critical bottleneck for organizations deploying agentic AI at scale.”
“Customers increasingly want the flexibility to build AI infrastructure using the technologies that best meet their requirements,” said Yossi Kikozashvili, Vice President, Head of Product & G2M, AI Infra at DriveNets. “The collaboration between DriveNets, AMD and VAST demonstrates how an open ecosystem can bring together best-in-class networking, accelerated computing and intelligent data infrastructure to support the next generation of AI factories.”
SOURCE: GlobeNewswire