A first GPU infrastructure investment
An assessment of sizing, deployment options and ownership costs before committing capital.
Sustainablemindz services
Consulting
A documented investment decision, grounded in workload and site requirements.
Illustrative infrastructure imagery
The scope
What's included
Capacity planning, vendor selection and data centre readiness from people who have bought and deployed GPU hardware.
- Capacity planning
- Model sizes, concurrency and growth assumptions
- Options analysis
- Buy, rent and hybrid comparisons
- Site readiness
- Power, cooling, space and connectivity
- Cost modelling
- Hardware, facilities, utilisation and operations
- Decision pack
- Trade-offs, priorities and phased next steps
Workload and capacity assessment
Translate models, data volumes and usage patterns into practical compute and memory requirements.
Build versus buy versus rent analysis
Compare deployment options against utilisation, budget, delivery timing and your operating model.
Vendor and configuration selection
Evaluate proposed systems against agreed technical and commercial criteria.
Data centre, power and cooling readiness
Identify site constraints and actions needed before high-density GPU equipment is installed.
Total cost of ownership model
Account for hardware, facilities, networking, support and operations with explicit assumptions.
Procurement strategy
Plan configurations, ordering phases and supplier questions around your project priorities.
From requirement to delivery
How it works
- 01
Define the decision
Agree the questions, constraints and evidence needed to make your investment decision.
- 02
Assess and compare
Review workloads, site readiness and available options using consistent criteria.
- 03
Recommend a path
Present findings, cost assumptions, trade-offs and a prioritised action plan.
- 04
Support the next step
Help your team interpret supplier proposals or prepare for procurement and deployment as agreed.
Example scopes, not customer case studies
Typical projects
A data centre readiness review
A review of rack, power, cooling and connectivity constraints for a proposed GPU installation.
A vendor proposal comparison
An evaluation of competing configurations, commercial assumptions and delivery risks.
Documented delivery
What you receive
The final deliverables are defined in your agreed scope.
- Requirements summary: workloads, model sizes, users and growth
- Sizing recommendation with GPU, OEM and cluster options compared
- Data-centre readiness assessment: power, cooling and floor space
- Buy, rent or hybrid recommendation with reasoning
- Phased roadmap with lead times and procurement steps
After handover
Support and assurance
Independent advice
We recommend what fits your workload – including smaller systems or renting when that makes more sense.
Follow-through
If you go ahead, the same engineers carry the design into procurement and deployment.
Clear documentation
Every engagement ends with a written report your board, finance and IT teams can use.
Before you start
Frequently asked questions
Buyer guide · 5 min read
Is your data centre ready for a GB300 NVL72 rack?
Build your next AI environment.
Share your workload, location and timeline. Start with a configuration quote or an engineering conversation.