AI Concepts

What is AI data residency?

AI data residency is the practice of keeping data associated with AI workloads — prompts, outputs, embeddings and logs — within a chosen legal jurisdiction or private environment. It matters for regulated industries and public-sector procurement, where cross-border transfers trigger legal obligations. Residency is a property of where processing and storage happen, not just where a contract is signed.

Key facts

DefinitionKeeping AI prompts, outputs, embeddings and logs within a chosen jurisdiction or environment
Why it mattersCross-border transfer rules, sector regulation and public-sector procurement conditions
What counts as dataInputs, outputs, embeddings, cached content, telemetry and audit logs
How to verifyContractual terms plus technical evidence of where processing and storage occur
Plugsky approachRegion selection plus VPC, on-prem and air-gapped deployment options
Related controlsBYOK for key custody, audit logs and DPA terms
StatusRegional and private deployment options are available; confirm the current regional list with sales or docs
Common trapAssuming a data-processing agreement alone satisfies a residency requirement

TL;DR

  • Residency covers prompts, outputs, embeddings, logs and telemetry.
  • A DPA is not the same as technical residency — verify where processing happens.
  • Region selection handles many cases; VPC, on-prem and air-gapped handle stricter ones.
  • Subprocessors and support access are part of the residency surface.
  • Document the evidence trail before procurement asks for it.

How it works, step by step

  1. Classify the data your AI workload touches, including logs and embeddings.
  2. Map each data class to the jurisdictions your policy permits.
  3. Ask the provider where inference, storage and support access occur — and get it in writing.
  4. Choose a deployment model: shared region, dedicated VPC, on-prem or air-gapped.
  5. Verify with technical controls: region pinning, private networking and audit logs.
  6. Re-review when models, features or subprocessors change.
1Classify the datayour AI workloadtouches, including2Map each data classto thejurisdictions your3Ask the providerwhere inference,storage and support4Choose a deploymentmodel: sharedregion, dedicated5Verify withtechnical controls:region pinning,6Re-review whenmodels, features orsubprocessors

Try it yourself

Open the AI data residency checklist →

What AI data residency covers

Residency is broader than the prompt you send. It includes the completion returned, any embeddings or fine-tuned artifacts derived from your data, cached content, telemetry, error traces and access logs. It also covers who can reach the data operationally — support engineers and subprocessors are part of the surface. A credible residency position names each of these and states where it lives.

When residency becomes a requirement

  • Regulated sectors: banking, healthcare, telecom and energy with localisation rules.
  • Public sector: procurement that requires in-country processing or sovereign operation.
  • Contracts: customer agreements that forbid cross-border transfer of specific data classes.
  • Critical infrastructure: environments where external network calls are prohibited.
  • Privacy commitments: public promises about where user data is processed.

The strictest case is air-gapped: no public internet at all, updates by controlled media.

Common mistakes

  • Treating a signed DPA as proof of residency without technical verification.
  • Forgetting embeddings, logs and backups, which often live in different regions from inference.
  • Overlooking support access — remote engineers in another jurisdiction can defeat an in-region deployment.
  • Assuming every feature is available in every region; roadmaps differ.
  • Documenting nothing, then failing a procurement audit that asks for evidence.

How Plugsky implements residency

Plugsky offers region selection and, for stricter requirements, deployment models that keep both data and serving inside your environment: VPC, on-prem and air-gapped. Because the API is OpenAI-compatible, applications do not change when the endpoint moves. Enterprise controls around key management, RBAC and audit logs complement the deployment choice, and documentation and status pages record the current regional and feature availability. Confirm the exact regional list and contractual terms for your jurisdiction during procurement.

Honest comparison

RequirementShared regional APIDedicated VPCOn-prem or air-gapped
Data locationProvider region you selectYour cloud account and regionYour facilities
Internet dependencyYesPrivate connectivityNone
Operational burdenLowestModerateHighest
Typical buyerCommercial appsRegulated enterprisesGovernment and critical infrastructure
VerificationContract plus region pinningNetwork and account evidenceFull physical control

Frequently asked questions

What is AI data residency?

Keeping data connected to AI workloads — prompts, outputs, embeddings, logs and telemetry — within a chosen jurisdiction or private environment, and being able to prove where processing and storage happen.

Is data residency the same as data sovereignty?

They overlap. Residency is about location; sovereignty adds legal and operational control, such as local ownership, local operation or immunity from foreign access laws.

Do embeddings and logs count as data?

Yes. Derived artifacts and records can be subject to the same transfer rules as raw prompts, and they are often stored in different systems, so map each separately.

How does Plugsky support data residency?

Through region selection and deployment options including VPC, on-prem and air-gapped, combined with key management, RBAC and audit controls documented on the enterprise and legal pages.

Does an OpenAI-compatible API change my residency options?

It helps: because application code does not change, you can move the endpoint to a private deployment in the required jurisdiction without a rewrite.

What evidence should I collect for an audit?

Deployment architecture, region pinning, network diagrams, subprocessor lists, access logs and the contractual terms that commit the provider to the arrangement.