Redaction before anything leaves your tenant.
Sensitive data is detected and replaced before any prompt reaches a model — and restored in the response, so the user sees real values while the model never does.
How it works.
The pre-AI step identifies sensitive entities — names, emails, phone numbers, IBANs, monetary values, dates — and replaces them with stable placeholders. The post-AI step reverses those placeholders in the response, so the user sees real values while the model never does.
What the employee wrote
I need to draft a termination letter for Marcus Heinonen (m.heinonen@nordic-logistics.fi), employee ID NL-4821. His last working day is 30 June 2026. His final salary payment of €67,400 should be transferred to IBAN FI21 1234 5600 0007 85. Please keep the tone professional but empathetic.
What the model received
I need to draft a termination letter for <PERSON_001> (<EMAIL_001>), employee ID <ID_001>. His last working day is <DATE_001>. His final salary payment of <MONEY_001> should be transferred to <IBAN_001>. Please keep the tone professional but empathetic.
What the user got back
Dear Marcus Heinonen, we are writing to inform you that your employment with Nordic Logistics will conclude on 30 June 2026. Your final salary of €67,400 will be transferred to your registered account ending FI21 1234 5600 0007 85 within the standard notice period.
Simple to start. Configurable when you need it.
Two tiers of redaction — one ready out of the box, one built for organizations with more complex needs.
Redaction
A few clicks to configure and switch on. Covers names, emails, phone numbers, IBANs, monetary values, and common dates — detected and reversed automatically. When something is detected, users see exactly what gets redacted before the message is sent.
Advanced Redaction
Everything in Redaction, plus the ability to define your own sensitive data types — internal codenames, project IDs, or any regulated terms your team cares about.
Try the Redaction Engine.
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