Help Enterprise Customers Accelerate AI Adoption

Implementing AI

The Enterprise Challenges

AI demand continues to accelerate across industries. While the benefits and productivity gains are appealing, enterprises struggle to know how to correctly set up infrastructure for their needs; demand scales up and down as workloads fluctuate. Tools evolve over time, and new possibilities arise. It can be difficult to keep pace, or to even get started.

Many enterprise customers face several challenges:

Fragmented tooling: Unpredictability and fragmentation result in a lack of resource visibility and utilization, leaving customers in the dark and struggling to optimize their workflows.

Complex infrastructure: Closed platforms, complex workloads across multiple configurations and a lack of performance optimizations slow enterprises down, and place bottlenecks on performance.

A lack of clarity around ROI: Enterprises ask themselves, “What is the extent of AI’s potential? How much should be invested to achieve what result(s)?” Without dedicated teams to drive AI, they lack a clear picture of what they can do with AI.

Ensuring AI implementations truly serve customer needs is vital for long-term adoption. AI remains fragmented across hardware and software environments, leaving customers to integrate solutions themselves. With the AMD Enterprise AI Reference Stack that’s no longer the case.  

A cohesive, modular platform built on open-source technologies, this stack enables enterprises to move AI from an experiment to a material impact on their business. Able to accelerate AI deployments, strengthen existing operations, and maximize ROI, the AMD Enterprise AI Reference Stack delivers on the promise of the hardware you support customers with and elevates the possibilities of AI in the enterprise space.

Powering Enterprise AI with Trusted Ecosystem Partnerships 

AMD is collaborating with leading OSV providers including VMware, Nutanix, Red Hat, Canonical and SUSE to deliver optimized enterprise AI solutions tuned for AMD hardware. Together, these partnerships help to enable scalable, secure and interoperable AI deployments across hybrid cloud, virtualized and on-prem environments while helping enterprises accelerate adoption with validated software stacks and optimized performance on AMD Instinct™ GPUs and infrastructure powered by AMD.

AI-Ready in Moments

AMD Enterprise AI Reference Stack Unpacked

The AMD Enterprise AI Reference Stack offers four distinct components, bundled together but offering modular freedom to customers who can select only what they need for their use cases. It’s simple to get started as well; customers can move from bare metal hardware to productive-grade AI in minutes.

AMD Resource Manager
AMD Resource Manager enables customers to own oversight and management over their infrastructure through various views and features, including the resource dashboard that offers an insightful high-level overview of clusters, GPU nodes and more. Customers can optimize their GPU utilization and cost control with intelligent workload scheduling, quota management and distributed scheduling with Ray integration, as well as actionable telemetry that enhances throughput, fairness and capacity planning across teams.

AMD AI Workbench
The AMD AI Workbench helps accelerate AI development and collaboration through dynamic workspaces, pre-built pipelines for fine-tuning foundation models, and inference deployment to streamline the journey from prototype to production.
Offering a library of open-source models optimized for AMD compute, and simplified deployments of interactive tools like Visual Studio Code and JupyterLab, the AMD AI Workbench unlocks rapid prototyping and development of AI applications in familiar IDEs for enterprises.

AMD Inference Microservices (AIM)
AIM provides pre-built, optimized containers that include AI models, inference engines and the specific configurations required to run on AMD platforms for faster, more efficient deployments. AIM supports open models and OpenAI-compatible APIs, along with intelligent hardware detection and tuning, for maximum performance and cost efficiency.

AMD Solution Blueprints
AMD Solution Blueprints provide pre-built validated designs that enable enterprises to accelerate project timelines, lower engineering costs, and implement repeatable production-ready solutions. Bridging the gap between raw AI models and functional business tools, these blueprints provide ready-to-go starting points for common enterprise AI applications.

The Benefits, Made Clear

Together, these four components close the friction gap between the possibilities AI can deliver to customers and the bottlenecks and resource gaps they currently face. Instead of delivering hardware alone, AMD partners can now deliver a complete production-ready solution to enterprise customers.

Easy Migrations: AMD Inference Microservices let existing customers on competitor platforms transition seamlessly, thanks to its hardware-aware containers that use OpenAI-compatible APIs. With the Enterprise AI Reference Stack, customers can get online and start using AI quickly, making migrations more streamlined.

Maximized ROI: AMD Resource Manager helps customers avoid idle GPUs and resource wastage, maximizing hardware investment and distributing compute resources efficiently across teams.

Better Productivity: The AMD AI Workbench lets teams test, fine-tune and deploy models directly to hardware, helping reduce time-to-production, ensuring investments in new infrastructure are optimized for ROI from day one.

Simplified Deployments: Your customers don’t need fleets of AI engineers, thanks to AMD Solution Blueprints. Ready to run, these reference designs handle the most common enterprise needs, from document research to automated coding assistants. Pre-validated by AMD to work on AMD hardware, they provide a streamlined way to help your enterprise customers get up and running quickly with AI workloads.

AI, Open for Everyone

Unlike proprietary alternatives, the AMD Enterprise AI Reference Stack is built around open technologies, letting customers own their stack and retain control over their installations.

If you’d like to learn more about the Enterprise AI Reference Stack and the possibilities it affords for your customers, speak to your AMD representative. 

Visit the AMD Enterprise AI Reference Stack page for more information.