What to Verify in a Secure AI Infrastructure Provider

Verifying a secure AI infrastructure provider means checking five dimensions — isolation, encryption, access, audit, and AI-specific data path controls — with evidence rather than accepting marketing claims, because a provider's security failure becomes your incident. For the full audit methodology, see auditing AI infrastructure providers. For the evaluation framework, see evaluating secure AI providers.

The Five Verification Dimensions

Isolation: verify the infrastructure is dedicated single-tenant, or shared with proven logical isolation. Demand GPU memory clearing logs and network segmentation evidence. Encryption: confirm in-scope surfaces — storage, transit, GPU memory — with key residency matching data residency. Access: verify who can reach your data, including provider staff. Demand the access scope, the controls bounding it, and the logging recording it. Audit: confirm logs cover all access and data movement events, including AI-specific events, and are tamper-resistant. AI data path: verify checkpoints, inference logs, vector databases, and GPU memory are governed with the same controls as traditional data. A provider that cannot produce evidence for all five is a provider whose security posture is unverified. For each dimension: demand documents, not assurances. For the evidence checklist, see auditing AI providers.

FAQ

What should I verify in a secure AI provider?

Isolation, encryption, access, audit, and AI data path controls — all five with evidence. No evidence means no verification. See the five dimensions above.

Summary

Verify a secure AI provider across five dimensions with evidence. For the full framework, see auditing AI providers.