Cluster Procurement & Build
GPU clusters represent nine-figure capital decisions with 18-month lead times and strategic consequences. The wrong choice on hardware architecture, vendor partnerships, or deployment topology can lock you into suboptimal economics for years.
What's included
Requirements Definition
What workloads will your cluster run? What scaling profile do you need? What's your unit economics sensitivity ($/H100/month, $/inference, etc.)? Disintermediate translates your business requirements into hardware specifications and helps you understand trade-offs between compute density, power, cooling, and network.
Hardware Evaluation
Disintermediate evaluates hardware options (GPUs, interconnect, server platforms, and ODM vendors) based on your workload, timeline, and cost structure. This includes performance modelling, availability assessment, and pricing comparison across generations and vendors.
Deployment Design
How will your cluster be deployed? Disintermediate designs cluster topology, rack architecture, network topology, power and cooling strategy, and multi-site/multi-region resilience. This includes software stack evaluation (CUDA, ROCm, PyTorch, vLLM, etc.).
Vendor & Procurement Strategy
Which vendors should you engage? How do you negotiate pricing and supply? Disintermediate helps you evaluate and negotiate with hardware vendors, ODMs, integrators, and logistics partners to secure best available pricing and lead times.
How we work
Requirements Workshop
Meet with your engineering and ops teams to capture workload requirements, scaling profile, cost structure, and timeline constraints.
Hardware Evaluation
Evaluate available hardware options. Performance modelling against your workloads, vendor availability, and pricing analysis.
Deployment Design
Design cluster topology, network architecture, power and cooling strategy. Software stack evaluation and multi-site resilience planning.
Recommendation & Presentation
Present recommended hardware configuration, deployment topology, vendor shortlist, and procurement strategy to your leadership.
Procurement Support
Support vendor negotiations, RFQ process, and technical validation of quoted configurations.
What you'll have at the end
Requirements Document
Detailed technical requirements for your cluster, workload profile, and cost structure.
Hardware Recommendation
Recommended GPU architecture, interconnect strategy, server platform, and scale profile with cost modelling.
Vendor Shortlist
2-3 recommended ODM or integrator vendors with competitive analysis and lead time assessment.
Deployment Plan
Detailed cluster topology, rack design, network architecture, power/cooling strategy, and deployment phasing.
Executive Presentation
Board-ready presentation of recommended approach, vendor options, and capital requirements.
Who engages on deployment advisory
- Cloud operators planning new GPU cluster deployments at scale
- Enterprises building captive GPU infrastructure for AI applications
- Research institutions deploying clusters for compute-intensive research
- Sovereign AI initiatives procuring hardware and deploying national infrastructure
- Large language model service providers scaling inference and fine-tuning infrastructure
Depending on deployment scale and complexity
On-site and remote engagement