The safest way to evaluate an AI infrastructure vendor is to test evidence against your exact workload, data, deployment and business risk—not to compare logos, headline accelerator counts or a corporate compliance badge. Define the job first, map every infrastructure dependency, require service-specific proof, run a workload-based proof of concept, and put measurable obligations and an exit path in the contract.
This process applies to GPU or TPU cloud capacity, managed clusters, colocation and deployment partners, and providers that bundle infrastructure with software or models. It also prevents a common category error: an AI application or model supplier may depend on infrastructure, but that does not make its application-level claims evidence about the underlying compute, storage, networking or tenant isolation.
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Start by defining the workload and the consequences of failure
Do not begin with a vendor presentation. Write a short requirements brief that describes what must run, where it may run and what happens when it does not. UK Government Guidelines for AI procurement recommends multidisciplinary preparation, discovery of available data and output-based requirements tied to user needs and required performance.
Describe the workload precisely
- Workload type: separate pre-training, fine-tuning, batch inference, interactive inference, retrieval, evaluation and mixed workloads. State whether jobs are scheduled, always-on or bursty.
- Scale: record model sizes, dataset sizes, expected concurrent jobs, accelerator-hours, storage growth and the proportion of time capacity is expected to be used.
- Performance: set end-to-end latency, throughput, time-to-first-token, job-completion and queueing targets where relevant. Do not substitute a peak accelerator number for an application result.
- Software: list frameworks, libraries, drivers, container images, orchestration, identity systems, observability tools and APIs that must interoperate.
- Data: classify personal, confidential, regulated and proprietary data; identify residency, transfer and retention requirements; and state whether logs, checkpoints or model weights have the same restrictions as source data.
- Resilience: define recovery-point and recovery-time objectives, acceptable maintenance windows, backup expectations and the consequence of losing a job, checkpoint or dataset.
- Operations: identify the skills your team has for cluster administration, security, FinOps, incident response and model operations, then state what you expect the supplier to operate.
- Commercial limits: specify budget assumptions, commitment tolerance, required purchasing route, currency and whether spending may vary with demand.
Include procurement, engineering, security, privacy, legal and domain specialists when the use case warrants it. A medical, public-sector or safety-critical deployment needs different evidence and contractual remedies from an internal experiment. The NCSC’s risk principle is direct: “The level of confidence you need in the security of a service is directly correlated with the impact to your organisation if your data were to be leaked or corrupted by the service, and the impact of the service being unavailable.”
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Separate infrastructure services from AI applications and models
An infrastructure supplier provides some combination of accelerators, servers, networking, storage, virtualization, containers, schedulers, orchestration, monitoring, security controls and operational support. An AI application or model supplier provides a trained model, an end-user product or an API. A single company can occupy both roles, but evaluate each role separately.
For an infrastructure purchase, ask who owns and operates each layer and who is accountable when a lower layer fails. A model supplier’s accuracy statement does not establish that its cloud region has sufficient capacity, that another tenant cannot read accelerator memory or that your data will be deleted on exit. Conversely, a cloud provider’s security attestation does not prove that a particular model is accurate, fair or suitable for your decision.
Map the complete stack and every dependency
Build an architecture map before comparing bids. The Cloud Security Alliance’s AICMv1.1 Auditing Guidelines for Cloud Service Providers calls for an inventory that reaches from GPU or TPU clusters through storage, networking, schedulers, virtualization and orchestration. The NCSC adds that a service built on another cloud must be assessed together with the underlying platform and the way the service configures it.
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|---|---|---|
| Accelerators and hosts | Accelerator model and generation, memory, interconnect, host CPU, firmware and availability by region | Which exact hardware is contracted? Can jobs move to another generation or region without notice? |
| Networking | Topology, bandwidth, latency, isolation, egress paths and cross-zone charges | What is measured end to end for distributed training and data access? |
| Storage | Object, block and file tiers, durability design, snapshots, backups, deletion and recovery | Where do datasets, checkpoints, logs and backups reside, and how are they sanitized? |
| Runtime and orchestration | Hypervisor or bare metal, containers, scheduler, quotas, queues, autoscaling and image registry | How are noisy neighbours, failed jobs and priority changes handled? |
| Operations | Monitoring, maintenance, patching, incident response, support and capacity management | Which team responds, within what time, and what telemetry can the customer see? |
| Subcontractors and underlying clouds | Legal entity, region, service dependency and responsibility split | Which controls are inherited, and how are changes or outages communicated? |
Require a current dependency diagram and a responsibility matrix. If a supplier refuses to identify a critical subcontractor or says that a badge covers “the platform” without naming the service and region, treat the claim as incomplete rather than assuming coverage.
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Turn sales claims into an evidence register
Create one row for every material claim: capacity, performance, availability, security, data handling, compliance, support, price or portability. Record the claim, its owner, the exact service and region, hardware and software assumptions, measurement period, exceptions, independent validation and expiry date.
| Evidence field | What good evidence contains |
|---|---|
| Scope | Named product, account tier, region, hardware, software version and included components |
| Recency | Test or audit dates, validity period and next review date |
| Method | Workload, dataset, traffic pattern, measurement definitions and exclusions |
| Independence | Internal report, customer-observed test, accredited assessment or independent audit, clearly identified |
| Exceptions | Out-of-scope controls, subcontractors, unavailable regions and customer responsibilities |
| Contract link | The clause, service level or remedy that makes the claim enforceable |
Ask for evidence attached to the contracted service, not a corporate-level certificate or a benchmark run on different hardware. NCSC guidance says the scope and freshness of certification matter more than the mere existence of a certificate and recommends recurring audits and current evidence. AI TrustMark’s 19 September 2026 guide makes the same practical point: match evidence to the exact product and deployment.
Run a proof of concept that resembles production
Set acceptance criteria before a proof of concept begins. Government procurement guidance recommends testing whether a proposed solution is likely to meet requirements, while the Data & Trusted AI Alliance (DTA) framework treats uptime, accuracy, resilience and integration as separate performance and reliability considerations.
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- Measure the whole path. Include data loading, preprocessing, queue time, accelerator execution, network transfer, storage access, post-processing and result delivery. Capture cost and operator effort alongside speed.
- Test steady state and bursts. Run normal utilization, a sudden demand increase, competing jobs and scale-out. Record queueing, throttling, autoscaling delay and whether the advertised capacity is actually obtainable.
- Exercise failure recovery. Interrupt a worker, revoke a credential, lose a storage path and simulate a regional or service dependency outage where the design permits. Measure checkpoint integrity, restart time, data loss and support response.
- Validate operations. Open a test support case, inspect logs and metrics, observe maintenance communication and confirm that your team can perform required administrative tasks.
- Document deviations. Record every concession, temporary setting and manual workaround. A result that depends on an uncontracted exception is not production evidence.
Do not present a vendor’s benchmark as your own test. No hands-on benchmark establishes a general winner here; your workload, region and configuration determine the result.
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Inspect security and tenant isolation at the infrastructure layer
Request architecture diagrams, control descriptions and test evidence for the exact accelerator and storage configurations you will use. The CSA auditing guidance highlights multi-tenant isolation, GPU or TPU memory protection, storage and network separation, runtime monitoring, data sanitization, incident response and compliance.
Identity and privileged access
- Require single sign-on or federated identity, phishing-resistant multifactor options where appropriate, short-lived credentials and role separation.
- Ask how provider administrators gain access, whether access is logged, how emergency access is approved and how quickly privileges are removed.
- Confirm that customer administrators cannot cross account, project or tenant boundaries.
Workload and accelerator isolation
- Ask whether workloads share hosts, accelerators, memory, interconnects or kernels, and what prevents one tenant from reading residual memory or cache data.
- Request the methodology and results of isolation tests on the proposed hardware, not a generic statement about virtualization.
- Determine whether bare-metal, confidential-computing or dedicated-capacity options change the threat model or price.
Network, storage and deletion
- Verify segmentation between management, storage and customer networks, private connectivity options, firewall ownership and egress controls.
- Map encryption in transit and at rest, key ownership, backup copies, snapshots, temporary files and logs.
- Obtain a deletion and sanitization procedure that covers failed disks, cached data, accelerator memory, replicas and termination.
Monitoring and incidents
- Specify which security and runtime logs you receive, their retention, time synchronization and export format.
- Ask how vulnerabilities are prioritized, patched and disclosed, including issues in drivers, images, orchestration and subcontractor services.
- Define incident severity, notification deadlines, investigation cooperation, evidence preservation and customer communications.
Scale this diligence to the harm caused by exposure or outage. A low-risk experiment may accept inherited controls; regulated or mission-critical data may require independent validation, customer audit rights and dedicated isolation.
Trace data governance, model provenance and responsibility
Draw a data-flow map from ingestion to deletion. Mark every place where source data, prompts, outputs, model weights, checkpoints, telemetry, backups and support tickets are stored or transmitted. For each item, record retention, region, encryption, access, subprocessors and whether it can be used to improve or train a provider’s service.
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For a managed model or AI service layered on infrastructure, request model version history, training-data provenance information that can lawfully be disclosed, evaluation methods, known limitations, bias and fairness testing, update notices and customer monitoring duties. OECD Due Diligence Guidance for Responsible AI (2026) treats compute, cloud and hardware companies as AI input suppliers in the value chain while recognizing that roles can overlap. That means an infrastructure contract should state what the provider knows, monitors and escalates about upstream and downstream risks rather than assuming another party owns every obligation.
Normalize total cost and business value
Obtain written quotes for the same configuration, region, workload and period. Current prices, accelerator availability, service regions and contract language change frequently; the reviewed guidance does not establish a comparable market price.
| Cost element | How to normalize it | Questions to include |
|---|---|---|
| Capacity | Compare on-demand, reserved or committed units using the same expected utilization and term | What happens to unused commitment and what capacity is guaranteed? |
| Accelerator and host time | Use completed jobs or useful output, not only hourly rates | Are licensing, host CPU, memory and interconnect included? |
| Storage | Include primary, snapshot, backup and retained-log volumes | Are minimums, API operations or recovery charges separate? |
| Networking and data movement | Model ingress, egress, cross-zone and cross-provider transfers | What charges apply during migration, backup or disaster recovery? |
| Software and support | Include orchestration, managed services, premium support and professional services | Which features are optional and which are required to meet the target? |
| Scaling and exit | Price bursts, idle periods, export, conversion, migration assistance and data deletion | Are there minimum terms, termination fees or assistance rates? |
Compare business value as well as spend. The DTA framework explicitly balances cost, impact, return on investment, risk, performance and reliability, and integration. A lower hourly rate can be more expensive if queueing, rework, outages or proprietary interfaces reduce useful output.
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Make the contract enforce the decision
Move every requirement that matters into measurable language. Generic security promises are difficult to enforce; NCSC guidance recommends specific security requirements, while ICO guidance supports accuracy KPIs or SLAs and clear processing responsibilities.
- Availability and capacity: define the service components covered, measurement method, exclusions, maintenance notice and remedies. If capacity is the requirement, specify allocation or fulfillment commitments rather than only an uptime percentage.
- Performance: state workload, percentile latency or throughput, queueing limits, test conditions and the remedy for repeated misses.
- Security: assign identity, patching, isolation, key management, logging, vulnerability handling and incident duties to named parties.
- Incident response: set severity definitions, notification windows, update cadence, cooperation, evidence access and post-incident reporting.
- Data: define location, retention, deletion verification, backup handling, subprocessor approval and restrictions on provider improvement or training use.
- Change control: require notice for hardware, software, model, region, subprocessor, pricing or interface changes, and identify changes that trigger buyer testing or approval.
- Audit and evidence: specify access to current attestations, test summaries, logs and independent assessments for the contracted service.
- Termination and remedies: define service credits or other remedies, suspension rights for serious risk, export assistance, deletion certification and treatment of outstanding commitments.
Test portability and plan the exit before signing
Government procurement guidance recommends strategies to avoid lock-in, including open standards and suitable procurement terms. Ask for an exit design while the supplier still wants your business.
- List the artifacts to export: raw data, metadata, labels, model weights, tokenizer files, checkpoints, feature stores, logs, configurations, infrastructure definitions and audit records.
- Identify the format and interface for each artifact, whether it is documented and whether another provider can import it without proprietary conversion.
- Run a small export and restore test, including permissions, checksums, lineage and recovery of a representative workload.
- Record time, bandwidth, staff effort and charges for a full migration. Include encrypted backups and data held by subprocessors.
- Define assistance, notice periods, continued read-only access, deletion deadlines and a final certificate of deletion.
Also ask how updates are announced. Hardware refreshes, driver changes, model revisions and orchestration upgrades can alter performance or reproducibility. Require release notes, deprecation periods, rollback or pinning options where feasible, and a right to retest material changes.
Use a common scorecard and record uncertainty
Score every candidate against the same evidence standard. A numerical score is useful only when each score points to a document, test result or contract clause.
| Decision axis | Evidence to score |
|---|---|
| Workload fit | Training, fine-tuning and inference support; accelerator and software compatibility; scale; latency; throughput; queue behavior |
| Availability and operations | Capacity certainty, resilience, maintenance, support, incident communication and recovery performance |
| Security and isolation | Tenant boundaries, privileged access, data protection, auditability, independent validation and evidence freshness |
| Data and governance | Location, retention, subprocessors, processing roles, logging, provenance, fairness information and monitoring duties |
| Integration and portability | APIs, current-system compatibility, open standards, export, migration effort and exit charges |
| Commercial fit | Normalized total cost, commitment flexibility, support, storage and network charges, business value and risk |
| Contract quality | Measurable service levels, responsibility split, change controls, remedies, audit access and termination assistance |
For each shortfall, record the impact, owner, mitigation, residual risk and trigger for reassessment. The DTA framework is intended for pre-contract assessment and complements specialist reviews; it does not require every shortfall to disqualify a supplier if the choice and safeguards are explained. Preserve the assumptions used in the score so a later hardware, region, workload or regulatory change can be evaluated consistently.
Questions to ask in the final vendor meeting
- Which exact service, region, hardware generation, software stack and subcontractors are included in this proposal?
- Can you show the complete path and retention period for data, model weights, checkpoints, logs and backups?
- What evidence demonstrates isolation between customers on the proposed accelerator, storage and network configurations?
- Which attestations cover this service and region, what period do they cover, and which controls or components are excluded?
- What workload-specific performance, queueing and availability commitments can be written into the contract?
- How are incidents, vulnerabilities, maintenance, capacity shortages and material service changes communicated?
- What are all usage, storage, network transfer, support, commitment and exit charges for our expected workload?
- How can we export data and workloads, and which standards or interfaces support migration?
- Which customer-side skills, tools and 24-hour responsibilities are required?
Recognize common warning signs
- A benchmark names an accelerator but not the model, software versions, dataset, concurrency, queue time or measurement method.
- A certificate is presented without the covered service, region, period, exceptions or underlying platform.
- “Dedicated” capacity is not defined for hosts, accelerators, memory, network or storage.
- Deletion covers the primary volume but not snapshots, backups, caches, logs or failed hardware.
- The supplier cannot explain who controls a subcontracted cloud or how a dependency outage is handled.
- Pricing excludes egress, storage growth, support, idle commitments or migration.
- Accuracy or fairness is discussed in marketing material but has no acceptance threshold, KPI, monitoring owner or update process.
- The contract allows material hardware, software, region or subprocessor changes without notice or retesting.
- Export is described as possible but no format, interface, test, time estimate or charge is specified.
Resolve a warning sign with a scoped document, demonstration, test or contract clause. If it remains unanswered, carry it as explicit residual risk rather than silently assuming the most favorable interpretation.
Keep the evaluation current
Vendor capability, accelerator supply, pricing, service regions and assurance evidence can change quickly. NVIDIA’s Requirements for AI Clouds version 2.4, updated 1 September 2026, is a provider-specific technical reference and not a neutral certification that every vendor meets it. UK procurement, NCSC, CSA, ICO, OECD and DTA guidance should likewise be applied to the buyer’s jurisdiction, sector, data and use case; UK guidance is not a substitute for local legal advice.
Set a review cadence and event triggers: a new region, hardware generation, model or subprocessor; a material incident; a repeated service-level miss; a regulatory change; a major workload shift; or a proposed price or interface change. At each review, rerun the affected evidence checks, update the scorecard and decide whether safeguards, contract terms or the provider itself must change.
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