What PII does your text leak to the LLM?
Paste a prompt, log line or API payload — see exactly what OpenAI, Anthropic or Mistral would receive, and what's left once the personal data is masked.
Why this matters
Every prompt you send to a cloud LLM — including the customer record, the log line, the support transcript — arrives at the provider (OpenAI, Anthropic, Google) in cleartext. A no-training flag doesn't change that: the data is still exposed to a third country and a third party.
Under the GDPR that's a transfer of personal data you may not have a basis for. The fix isn't "stop using AI" — it's masking the PII before the request leaves your service, and un-masking the response.
That's what Saklam Bridge is — the engine from this tool as a Docker container in your own infra. As a proxy (one line: base_url) or as a Mask API, on-prem.
Chat with a real AI model right here — masked? Drop your email, type in the code, go: €1 free credit, 7 days. Your messages are masked in your browser before they reach the model — we see nothing.
No spam. No password. Email only for access.
We sent a 6-digit code to — type it in and the chat opens right here.
Personal data is replaced with placeholders in your browser — the model never sees it. The response is restored locally; "what the AI saw" shows you the actual upstream.
Your demo credit is used up. This exact thing keeps running unlimited in your own infrastructure — as a Docker container, with your API keys, any LLM:
Saklam Bridge — €99/mo →Rather run it in your own infrastructure right away? Saklam Bridge (Docker) →
How this page works
Detection runs entirely in your browser via Saklam's PII engine (350+ validated patterns across EU-27 + EEA + UK, plus a multilingual NER model for names). Your text never touches our server. No logs. The model is loaded once from saklam.com (noez GmbH, EU) and cached locally — offline after first load.
