Key facts
| Security controls | SSO/SCIM, RBAC, encryption with BYOK, SIEM audit export |
| Residency | Region-locked planes: EU, GCC, APAC, US; verify store-level mapping |
| Subprocessors | Published list with change notification in the DPA |
| Deployment models | Cloud, VPC, on-prem, air-gapped — reduces shared-tenancy risk |
| Availability | Automatic upstream failover; 99.9% uptime on paid plans; 4-hour Enterprise support SLA |
| Compliance posture | SOC 2 Type II and ISO 27001 readiness in progress (not yet certified); GDPR and PDPL alignment |
| Contract terms | Terms at /legal/terms; DPA with audit rights, deletion and breach notice |
| Status | Live API with 30+ models; component health published |
TL;DR
- Score upstream model dependencies separately — they are a distinct concentration risk.
- Require a current subprocessor list with locations and change-notification terms.
- Verify residency at store level, including logs, vectors and backups.
- Test availability claims against the SLA and the status page history.
- Assess exit before signing: export formats, deletion evidence and transition help.
How it works, step by step
- Define the risk domains and a scoring rubric before sending the questionnaire.
- Collect evidence: control descriptions, region maps, subprocessor list, DPA, SLA, status history.
- Assess the model supply chain: which upstreams serve each model, and what happens on deprecation.
- Review data governance: logging defaults, training use, retention and deletion.
- Evaluate resilience: failover design, region strategy, capacity and incident process.
- Score residual risk and document mitigations or acceptance decisions.
- Schedule periodic reassessment and trigger reviews on material changes.
Original data
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The seven domains
- Security — encryption, access control, vulnerability management, penetration testing.
- Data — classification handling, residency, retention, training exclusion, deletion.
- Supply chain — subprocessors and upstream model providers, with locations and change terms.
- Availability — architecture, failover, SLA, incident history.
- Contract — liability, indemnity, audit rights, breach notice, exit assistance.
- Vendor stability — financial health, key-person risk, roadmap coherence.
- Exit — portability, formats, deletion certificates and knowledge transfer.
AI-specific risks to score explicitly
Two risks are unique to AI vendors. Model dependency: the model you rely on may be served by an upstream provider that changes terms, retires a version or alters routing. Ask for the fallback chain and deprecation notice period. Data reuse: confirm whether prompts, completions or embeddings can influence training, and how that is enforced and audited. Plugsky documents automatic failover and a DPA covering subprocessors and deletion, and publishes a model catalogue with 30+ models; validate the specifics that matter to your risk committee.
Scoring and residual risk
Score each domain on evidence strength, not vendor confidence. A control description with sample outputs is stronger than a policy statement. Record residual risk after mitigations, assign an owner, and set review dates. Where certifications are in progress — as with Plugsky's SOC 2 and ISO 27001 readiness — attach a milestone and monitor it, or compensate with private deployment and BYOK.
Ongoing monitoring
- Subscribe to subprocessor change notifications and status updates.
- Review audit evidence at least annually.
- Track model deprecations affecting your workloads.
- Re-test deletion and access reviews on a schedule.
- Re-score when the vendor changes regions, models or ownership.
Honest comparison
| Capability | Plugsky | Hyperscaler AI platform | Building in-house |
|---|---|---|---|
| Subprocessor transparency | Published list with change notification | Per-service subprocessor pages | You vet each supplier |
| Model supply chain | Fallback chains across 30+ models | Vendor-controlled catalogue | You manage every model |
| Residency evidence | Region-locked planes and workspace selection | Region configuration per service | Your design |
| Audit export | SIEM connectors | Native cloud audit | Custom pipelines |
| Deployment isolation | VPC, on-prem, air-gapped options | Shared cloud by default | You own the stack |
| Certifications | SOC 2 / ISO 27001 readiness in progress | Completed audits in many regions | Your own programme |
Frequently asked questions
What makes AI vendor risk different from SaaS risk?
Two factors: upstream model dependencies you do not contract with directly, and data reuse questions around prompts, completions and embeddings. Both need explicit assessment.
How do we assess upstream model providers?
Ask for the mapping of models to upstream providers, their locations, the fallback chain, and the deprecation notice process. Treat concentration on a single upstream as a scored risk.
What evidence should replace a missing certificate?
Control descriptions, penetration-test summaries, architecture diagrams, configuration exports, audit samples and contractual remedies. Document residual risk after mitigations.
How often should we reassess?
At least annually, and on material change: new regions, new subprocessors, model deprecations, ownership changes or significant incidents.
Can we reduce risk with deployment choice?
Yes. Private endpoints, on-prem and air-gapped tiers remove shared-tenancy exposure and give you control over data and keys.
What exit clauses matter most?
Export formats for data and prompts, transition assistance, deletion certificates, and continued access during migration. Negotiate them before signature.
Where can we verify availability claims?
Compare the SLA at /legal/sla with the incident history shown on /status and with your own monitoring during a pilot.