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LLM Platformları 10 August 2026 · 5 min read

Data Privacy and Boundaries When Using LLMs

What to watch for on data protection and trade secrets when sending corporate data to a model.

LLM Data protection Privacy Security

Sending text to a language model means transferring it to a third party. That technically simple step has a legal counterpart.

01. Classification First

Which data can go to a model and which cannot? No enterprise AI project proceeds safely without that answer in writing. The public, internal and confidential split works here too.

02. The Enterprise Contract Difference

The most critical difference between consumer versions and enterprise plans is whether your data is used in model training and how long it's retained. Enterprise agreements state these clauses explicitly; free tools generally don't.

03. Data Residency

Which region data is processed in is decisive under Turkey's data protection law. If a cross-border transfer is involved, explicit consent or an undertaking is required. Providers offering region selection resolve this step up front.

04. Masking

Masking personal data before sending it to the model is possible in most scenarios. Turning names, phone numbers and ID numbers into placeholders and mapping the answer back removes most of the risk.

05. Shadow Usage

The biggest risk usually isn't in the approved system but in tools employees use with personal accounts. Banning doesn't work; offering a corporate alternative and writing a clear policy does.

06. Record Keeping

Which data went to which model must be logged. In an audit or an incident investigation these records are your only basis.

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