What should you check before using offshore compute for private AI?

Updated November 2, 2026. Facts checked November 2, 2026.

Short answer

Before using offshore compute for private AI, check four things: which country's law applies to your data on that host, who at the host can access the machine, whether you control the model and its weights, and how you get your data back if you leave. Price alone is a poor reason to move private work offshore, because a host that is cheap but opaque can cost more in exposure, lock-in, or an exit you cannot complete.

Law, access, and jurisdiction

The first question is not the hourly price but the legal regime. Data stored or processed in another country may be subject to that country's laws, to the laws of the country where the host company is based, and to any agreement you signed. If you handle regulated or sensitive data, that tangle may rule out a host before any technical test, and no marketing claim about privacy changes the law.

The second question is access. Ask who at the host can log into the machine, whether support staff can read your disks, whether the host keeps logs of your traffic, and how it responds to government requests. A host that cannot answer those questions in writing is not a private host, whatever its homepage says. Prefer a host that offers full-disk encryption you control, and confirm what happens to the disks when the server is returned or destroyed.

Model control and exit

Private AI is only private if you control the model. If the host supplies the model, limits which models you can run, or logs your prompts for its own purposes, you have rented a service, not a private machine. Running your own open-weight model on a machine you administer is a different arrangement, and the contract should say so, including whether the host claims any right over your prompts or outputs.

Exit is the test most buyers skip. Before signing, ask how you export your data, how long the export takes, what format it arrives in, and what the host deletes when you leave. A host that makes entry easy and exit hard is a lock-in risk, and that risk grows with every month of conversations and agent state stored only on its disks. Keep a current copy of your data somewhere you control, not only on the host.

A practical checklist

Write down the data you will actually put on the host, and the harm if it leaked. That list decides whether offshore compute is even in scope. Then ask the host, in writing, for its jurisdiction, its access policy, its logging policy, and its exit and deletion procedure, and keep the answers with the contract. If any answer is vague, treat that as a no, not as a detail to resolve later.

Finally, test the exit before you depend on the host. Move a small, non-sensitive workload, export it, delete it from the host, and confirm the deletion. That single test tells you more about a host than a pricing page, and it is cheap compared with discovering, during a real move, that your data cannot leave cleanly.

Before you sign

Ask the host, in writing, for its jurisdiction, its access and logging policies, and its exit and deletion procedure, and keep those answers with the contract. Vague answers should be treated as a no.

Test the exit with a small, non-sensitive workload before depending on the host. Export it, delete it from the host, and confirm the deletion, so a real move does not become a discovery exercise.

Frequently asked questions

Is offshore compute automatically less private?

No, but it is not automatically more private either. Privacy depends on the host's jurisdiction, its access and logging policies, and whether you control the machine and the model, not on the flag on the datacenter.

What is the biggest risk of offshore compute for private AI?

Usually lock-in or unclear access, not price. A host that cannot explain who can read your disks, or how you export and delete your data, is a risk even if its hourly rate is low.

Should you keep a copy of your data off the host?

Yes. Keep a current copy somewhere you control, so a host failure, a billing dispute, or a difficult exit does not become a data loss.

Sources

• NVIDIA sizing guide — AI vWS Toolkit, fine-tuning large language models
• Hugging Face — efficient inference on a single GPU

This page is general information only, not legal, tax, or financial advice. Confirm the figures for a specific property or system with the official source or a qualified professional.