AI Workload Management & Multi-tenancy Market Scan Workshop
In today's dynamic enterprise environments, managing AI workloads and ensuring effective multi-tenancy requires high-performance, resilient, and scalable solutions that can support digital transformation, hybrid work, and emerging application needs. Whether it's optimizing AI workload distribution, enabling seamless multi-tenant access, or ensuring secure segmentation and automation, selecting the right AI workload management solution is crucial. However, navigating the landscape of vendor offerings can be daunting. To simplify this process, our AI Workload Management & Multi-tenancy Market Scan Workshop combines deep vendor expertise, hands-on lab insights, real-world client use cases, and rigorous evaluation frameworks, helping to identify the best-fit solution for your organization.
What to Expect
This interactive 4–8-hour workshop can be delivered as a single session or broken into several focused modules:
- Discovery & Use-Case Interview: We begin by understanding your current requirements for AI workload orchestration, cluster management, and multi-tenancy of your GPU cluster(s), the key business drivers, and specific use-cases such as heavy inference, or training and fine-tuning. Plus, how you would prefer to drive a user experience.
- OEM Capability Assessment: Leveraging our research and lab-tested benchmarks, we evaluate several OEMs that have a proven solution in the AI workflow orchestration and multi-tenancy arena.
- Weighted Criteria Matrix: More than simple feature lists, we evaluate based on the following categories to ensure we encompass the best experience for you through the evaluation process. The categories include: job management, digital experience, security, and administrative features, to name a few.
- Solution Down-Selection: We help narrow your options to the top 2–3 OEMs that align most closely with your requirements and strategic roadmap.
- Deliverable & Next Steps: You'll receive a comprehensive report featuring definitions, visual matrices, and a clear recommendation. This serves as a decision-making blueprint and can inform future Proofs-of-Concept (POCs) or lab evaluations in our AI Proving Ground.
Goals & Objectives
- Accelerate Decision-Making: Save weeks of trial and comparison—focus only on the best-fit OEMs that match your weighted criteria.
- Bridge Teams for Alignment: Collaborate across AI practitioners, security, and IT operations to align priorities and ensure cross-functional buy-in.
- Leverage Expert Insight: Gain from analysts' benchmarks, real-world lab testing, and a neutral, vendor-agnostic evaluation approach.
- Enable Strategic Planning: Use the results not only for selection, but also to inform deployment strategies, integration plans, and even procurement roadmaps.
Who Should Attend?
- AI practitioners
- IT Infrastructure and Operations Leaders
- Security and Compliance Stakeholders
- CIOs or Business Unit Leaders interested in digital transformation
Benefits
| Benefit | Description |
| Focused OEM Comparison | Tailored evaluation focuses only on metrics that matter to your GPU deployments. |
| Cross-Team Engagement | AI practitioners, security, and IT leadership align around a clear, business-driven decision framework. |
| Trusted Advisory | Enables deeper collaboration, leveraging objective analysis, and best practices. |
| Cost-Effective Pre-POC Strategy | Minimize time and spending in lab testing by narrowing solutions before hands-on validation. |