GDPR-Ready AI Inference: Data Residency, Retention, and Auditability in Multi-Cloud

TL;DR: GDPR for inference APIs boils down to region pinning, minimal retention, and provable access controls. This turns legalese into engineering checklists.

What GDPR means in practice

You’re typically a processor of user data; you need mechanisms to keep data in the chosen region and erase it within defined windows; you must maintain records of processing (who accessed what, when).

Region & residency

• Region selection per workspace/environment; region lock to prevent cross-region failover.

• Keep weights, caches, logs in region-scoped storage.

• DR plan that keeps copies within the same legal area.

Data minimization & retention

• Redact payloads at ingress when possible.

• Default short retention (7–30 days) with per-workspace overrides.

• Verified deletes across primary + backups; API to erase by workspace/request ID.

• Avoid logging full prompts/responses by default.

Access control that proves itself

• SSO (SAML/OIDC) with MFA; RBAC scoped by org/workspace; least-privilege keys.

• Audit trails for console actions, API calls, and exports, including actor, scope, and before/after.

DPAs & sub-processors

Publish a list; allow EU-only telemetry or disable it; provide audit-log export for evidence.

Example EU-only setup

Create EU workspace → enable Region Lock → set Retention = 14 days → SSO + RBAC → export audit logs weekly to EU SIEM.

Shared responsibility

You own data you send, redaction choices, and tenant keys. We provide regional isolation, encryption in transit/at rest, access controls, auditability, and deletion APIs.