Why your AI data must stay in Türkiye

A compliance and infrastructure guide for enterprise teams: where does the data go, what do the rules say, and what does local infrastructure actually buy you?

An AI project usually starts small. A team sends a few requests to an off-the-shelf model, the results look good, and the project grows. The problem shows up on the day it goes live, when legal asks a single question. Where is this data going?

This post answers that question and explains what local infrastructure changes in practice.

Data changes country without you noticing

Every request you send to a model provider abroad travels to that provider's servers together with its content. That content usually looks harmless. In real usage, though, it ends up carrying:

• Customer names, phone numbers and email addresses
• Contract and invoice text
• Health, credit or HR records
• Internal correspondence and unannounced plans

Under Turkish data protection law these are personal data, and often special categories of personal data. Transferring them abroad requires a separate legal basis.

Three concrete risks

1. A transfer basis is hard to establish. Moving personal data abroad requires explicit consent, an undertaking, or an adequacy decision. None of these is resolved as quickly as an API call.

2. Auditors ask for evidence. When an auditor asks where your data is processed, a dropdown on a provider's region selector does not count as evidence. They want contracts, logs and an architecture diagram.

3. Latency accumulates. Every request to an endpoint abroad adds latency proportional to network distance. On a single request that is a few hundred milliseconds. In a chained agent workflow the same delay repeats dozens of times, and the user feels all of it as waiting.

What local infrastructure changes

When you run the model in a data centre in Türkiye, three things are solved at once:

• The transfer problem disappears. Data is processed inside the country, so cross-border transfer rules never come into play.
• Audits get easier. You hand over the data centre address, the contract and the access logs in one file.
• Latency drops. The request goes to a server in the same country. In chained workflows the difference compounds.

Five questions to ask before you sign

Ask for written answers to these before choosing a provider:

1. In which country and which data centre is my data physically processed?
2. Is the content of my requests stored? If so, for how long?
3. Is my data used to train any model?
4. Do you sign a data processing agreement?
5. Who can access the infrastructure, and is that access logged?

If there are no clear answers to these five questions, the problem you hit at launch will be legal, not technical.

In short

The most expensive mistake in AI projects is leaving data location until last. Building the architecture locally from day one is always cheaper than migrating later. That is exactly why baykAI provides GPU capacity and model services from data centres in Türkiye.