Pseudonymization and AI
How your data is masked before sending, and how to verify everything.
How pseudonymization works
Three local detection layers, stable tokens, and a mapping table that never leaves your machine.
Review detections before sending
Dismiss a detection, catch a missed term, and guarantee that the approved preview is what leaves.
Choosing an AI model
Managed models with your account, your own API keys, or a fully local model with Ollama.
Verify what goes over the network
Send badge, exact payload, audit log and token probe: trust is meant to be verified.
The local reading sheet
A structured analysis of your documents, produced by a model running on your machine, no network involved.
The six confidentiality levels
What you declare before sending, what each notch means, and the two that change how the app behaves.
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