GPU Procurement Without the Guesswork
Your AI initiative depends on compute you don't yet control. The GPU infrastructure market has 120+ providers, opaque pricing, and contract structures designed to favour sellers. You need an independent advisor who knows what good looks like - and what to avoid.
Clarity at every stage of GPU procurement
- Vendor evaluation and shortlisting: Independent assessment of GPU cloud providers against your workload, compliance, and geographic requirements. No vendor affiliations, no referral fees.
- TCO and build-vs-buy analysis: Full cost modelling across on-premise, colocation, and cloud options - including hidden costs like egress, networking, support tiers, and contract lock-in penalties.
- Contract review and negotiation support: Analysis of pricing structures, SLA terms, committed-use discount traps, and exit provisions. We know what operators actually offer versus what they list.
- Compliance and security alignment: Mapping provider capabilities to your SOC 2, ISO 27001, HIPAA, or data residency requirements. Understanding which certifications are real and which are marketing.
- Architecture guidance: Single-tenant vs multi-tenant trade-offs, inference vs training cluster design, and scaling path planning for 12-36 month compute roadmaps.
Why enterprise GPU procurement is broken
Opaque Pricing
Listed rates bear little resemblance to negotiated rates. Egress fees, support tiers, and networking charges inflate costs 30-60% above headline GPU pricing. Without benchmarks, you overpay.
Vendor Lock-In by Design
Committed-use discounts, custom integrations, and proprietary orchestration layers are designed to increase switching costs. By the time you realise, migration is a six-figure project.
Compliance Theatre
Many GPU providers claim SOC 2 and ISO 27001 compliance while operating shared infrastructure with minimal physical or logical isolation. Certifications need verification, not assumption.
Information Asymmetry
Providers know exactly what competitors charge, how capacity flows, and which customers are price-sensitive. Buyers rarely have access to comparable market intelligence.
How Disintermediate supports enterprise procurement
Strategy Advisory
Define your compute requirements, evaluate build-vs-buy, and design a procurement strategy aligned to your AI roadmap. Includes vendor landscape mapping and shortlisting.
Learn more →Financial Modelling
TCO models benchmarked against live market data. Compare on-premise, colocation, and cloud across 3-5 year horizons with sensitivity analysis on utilisation, pricing, and refresh cycles.
Learn more →Deployment Advisory
Technical architecture review, cluster design, and vendor evaluation for on-premise and colocation deployments. Hardware selection, networking topology, and cooling requirements.
Learn more →Retained Advisory
Ongoing market intelligence, pricing benchmarks, and strategic counsel as your compute needs evolve. Quarterly reviews, ad-hoc support, and contract renewal preparation.
Learn more →What enterprise buyers ask us
- Should we build on-premise, colocate, or use GPU cloud - and at what scale does the calculus change?
- Which providers can actually deliver on SOC 2, ISO 27001, and data residency requirements - not just claim them?
- What should we actually pay per GPU-hour for our workload profile, and how do we negotiate below list price?
- How do we avoid vendor lock-in while still capturing committed-use discounts?
- What does a realistic 3-year TCO look like, including egress, networking, support, and refresh cycles?
- Single-tenant or multi-tenant? What are the real security and performance trade-offs?
Enterprise buyers at every stage
- AI and ML teams scaling from cloud experimentation to production GPU infrastructure
- CTOs and infrastructure leads making build-vs-buy decisions on GPU compute
- Procurement teams evaluating GPU cloud vendors for the first time and needing market context
- Regulated enterprises (financial services, healthcare, government) requiring compliant GPU infrastructure
- Corporate AI programmes planning multi-year compute roadmaps and budgets
Enterprise procurement intelligence
Sovereign AI Procurement
National compute strategies, data sovereignty requirements, and the regulatory landscape for sovereign GPU deployment.
Single-Tenant GPU Clusters
When isolation matters. Security, performance, and cost trade-offs in dedicated GPU infrastructure.
On-Prem vs Cloud GPU
The build-vs-buy calculus for enterprise GPU compute. TCO breakpoints, operational overhead, and scaling economics.
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Procuring GPU compute? Get independent advice first.
We'll help you evaluate providers, model total cost of ownership, and negotiate contracts that protect your interests.
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