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Data residency and self-hosting for AI workflows in the UAE and Saudi Arabia

Where AI workflow data actually goes, what the UAE and Saudi personal data laws say about moving it abroad, and a checklist for choosing a deployment.

By The Cadrix team8 min read
A long aisle between rows of equipment cabinets in a server room
Photo by İsmail Enes Ayhan on Unsplash

If you run AI workflows in the Gulf, someone will eventually ask: where does the data go? The question sounds simple. The answer has several parts, because an AI workflow moves data in more places than a typical application.

This post maps those places, summarises what the UAE and Saudi personal data laws say about transfers abroad, and gives you a checklist for choosing between hosted and self-hosted deployment.

This is a practical guide, not legal advice. Laws and guidance in this area change. Every legal point below links to its source, and you should confirm with a qualified adviser before you decide.

Where data goes in an AI workflow#

Trace one customer request through a workflow and you will find at least five places where data rests or travels:

  1. The platform database, where the workflow definitions, run records and traces are stored.
  2. File storage, for uploaded documents and generated files.
  3. The model provider, which receives the prompt, including any personal data or documents you put in it.
  4. The knowledge store, a vector database holding chunks of your documents, plus the embedding provider that turned them into vectors.
  5. Connected systems, such as email, WhatsApp, payment or CRM tools, each with its own location and terms.

Residency is not one decision. You can host the platform in-country and still send every prompt to a model in another region. Map all five before you answer a regulator or a customer.

What the UAE law says about transfers#

The UAE's federal personal data protection law is Federal Decree-Law No. 45 of 2021 (the PDPL). A US Department of Commerce market intelligence page, dated January 2024, summarises its cross-border rules:

  • Article 22: personal data may be transferred outside the UAE to a country with an adequate level of protection, with the approval of the UAE Data Office. The page describes adequacy as the destination having data protection legislation or having joined bilateral or multilateral agreements on personal data protection.
  • Article 23: where the destination does not have adequate protection, transfers are allowed in limited cases. The page lists examples such as a binding contract or agreement, the data subject's express consent, performance of a contract, and international judicial cooperation.

The same page said the law's executive regulations were expected to be published during 2024. We could not confirm from official sources that they have been issued, and commentary we reviewed disagreed. Check the UAE legislation portal and the UAE Data Office for the current position before you rely on any detail.

Two further points to raise with your adviser. The UAE's financial free zones, DIFC and ADGM, have their own data protection regimes. And some sectors, such as health and finance, can have separate rules on where data may be stored. We have not reviewed those here.

What the Saudi law says about transfers#

Saudi Arabia's Personal Data Protection Law (PDPL) is administered by SDAIA, the Saudi Data and AI Authority. Based on SDAIA-hosted documents:

  • Article 29 of the law restricts transfers of personal data outside the Kingdom to listed purposes, such as performing an agreement to which the Kingdom is a party or serving the Kingdom's interests, or other purposes set out in the regulations. It adds conditions, including that the transfer does not harm national security or vital interests, that there is an adequate level of protection abroad as assessed by the competent authority, and that it is limited to the minimum data needed.
  • The Regulation on Personal Data Transfer Outside the Kingdom sets out when controllers may rely on appropriate safeguards, such as standard contractual clauses or binding common rules, and requires a risk assessment in specified cases. Law firm summaries say an amended version was published on 1 September 2024. Summaries also report that SDAIA will publish a list of countries considered to offer adequate protection.

Because translations and amendments differ, read the current official Arabic text, or an authoritative English version, before you design around these rules.

What this means for AI workflows#

Without giving legal conclusions, the laws above raise the same practical questions.

Is personal data going to the model provider? If a prompt contains a customer name, ID number or case details, and the provider processes it outside the country, that may count as a cross-border transfer. A prompt with no personal data does not raise the same question. Minimise what you send: pass only the fields the step needs, and mask what it does not.

Where do vectors and traces live? Chunks of personal documents stored in a vector database are personal data too, and run traces contain whatever the steps handled.

What is your lawful basis and contract? If you rely on contractual clauses or consent for transfers, make sure the agreements with your platform, model and connector providers actually exist and cover AI processing.

Deployment options#

Hosted service. Fastest to start. Cadrix's hosted service runs on a server operated by Hetzner Online GmbH in Falkenstein, Germany, according to our security page. If your policy requires data to stay in the Gulf, that is not suitable for that data.

Self-hosted, on-premises. Cadrix Enterprise runs on your own Linux or Windows servers, with your database and file storage, behind your network and access rules, and is activated with a signed licence file verified on the server, so a closed environment does not need to contact a licensing service.

Private cloud. The same software in a cloud account and region you control, such as a regional data centre of a provider you already use.

Model location. In any of these, the model is a separate choice. Cadrix is bring-your-own-model-key. In a closed network you can point workflows at an internal model endpoint, so prompts never leave your environment. If you use a hosted model, calls leave your environment for that provider only.

Note what self-hosting does and does not do. It keeps the platform's data under your control, but it does not remove your obligations as the data controller, and it makes you responsible for patching, backups and monitoring.

A checklist before you decide#

  1. Classify the data each workflow handles: personal, sensitive, confidential, public.
  2. Map the five places data rests or travels, for each workflow.
  3. Decide per class what may leave the country, and under which legal route.
  4. Check the model path. Which provider, which region, which retention and training terms?
  5. Minimise the prompt. Send fields, not documents, where possible.
  6. Control credentials. Keep keys in an encrypted store; never in prompts. Check who can read them.
  7. Set log retention and restrict who can open traces.
  8. Plan backups and recovery in the same jurisdiction as the data.
  9. Document the decision: who approved, what law and advice it rests on, and a review date.
  10. Get legal sign-off on the transfer basis, and revisit when regulations change.

Building a workflow that respects the boundary#

In Cadrix, you can enforce much of this in the design:

  1. Start with an Agent or LLM step that receives only the fields it needs, and use a Custom Function to mask identifiers before the model call.
  2. Use a model connection that points to an in-country or internal endpoint for steps that handle personal data, and a hosted model for steps that do not.
  3. Keep a knowledge base for policies and public information separate from personal records.
  4. Add a Human Input step for any workflow that sends personal data to an outside system or party.
  5. Open the run trace to confirm what each step received, and spot-check for personal data that should have been masked.

Sources#

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