Solution Design

Infrastructure Designed for Your Exact Requirements

Generic hardware configurations are a starting point, not a solution. Every AI deployment has unique requirements — specific workloads, budget constraints, space limitations, power envelopes, and performance targets. DVUN's Solution Design service creates a custom hardware architecture matched precisely to what you're building, not what's easiest to sell.

What Solution Design Delivers

  • Workload Analysis — We start by understanding your actual workloads: training vs. inference, model sizes, batch sizes, latency requirements, and throughput targets.
  • Hardware Architecture Design — A complete hardware stack specification: GPU servers, networking, storage, and facility infrastructure — selected and configured for your workload profile.
  • Budget Optimization — We design to your budget, identifying where to invest for maximum performance impact and where to save without compromising your requirements.
  • Scalability Planning — Architecture designed to grow with you. We plan for your current needs and your 12-24 month trajectory.
  • Vendor-Neutral Recommendations — We recommend what's right for your workload, not what has the best margin. DVUN's sourcing network means we can deliver on any recommendation we make.
  • Bill of Materials — A complete, itemized hardware specification ready for procurement — with DVUN or independently.

The Solution Design Process

  1. Discovery call — A 30-60 minute conversation to understand your workloads, requirements, constraints, and timeline.
  2. Architecture design — DVUN's team designs your hardware stack, typically delivered within 3-5 business days.
  3. Design review — We walk you through the architecture, explain the reasoning behind each decision, and answer questions.
  4. Iteration — We refine the design based on your feedback until it's right.
  5. Procurement — Proceed to quote and procurement with DVUN, or take the BOM independently.

Who This Service Is For

  • Organizations planning their first significant AI infrastructure deployment
  • Teams scaling from a single node to a multi-node cluster
  • Enterprises migrating AI workloads from cloud to on-premise
  • GPU cloud builders designing their initial infrastructure
  • Anyone who wants expert validation before committing to a significant hardware investment

Start Your Solution Design

Tell us what you're building and we'll schedule a discovery call to get started.

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