What is Privatiser and what does it do?

Privatiser is a browser-based tool that strips sensitive data out of text before you paste it into an AI chatbot. It detects things like API keys, passwords, IP addresses, and personal identifiers, replaces them with pseudonyms, and keeps a local mapping so you can restore the real values later. Everything runs in your browser — the site states that nothing leaves your machine and that it sends 0 bytes to any server.

It fits a specific situation: you want an AI to help with a config file, a log snippet, a database connection string, or a support ticket, but the text contains secrets or personal data you can't share. Privatiser lets you hand over the useful structure without the sensitive values.

How the anonymize-and-restore loop works

The workflow has two halves, and the second is what makes it usable for real tasks:

1. Anonymize — paste text into the input. Privatiser detects matching patterns and replaces each one with a pseudonym. You get a redacted copy plus a local mapping (shown as a mapping count, with options to copy or download the JSON).
2. Send the redacted text to the AI — the structure is preserved, so the model can still reason about your config, code, or data shape.
3. Deanonymize — paste the AI's reply back into the Deanonymize panel. Using the last mapping (or loading one from a file), every pseudonym snaps back to its real value.

The mapping is the key mechanism: it's what separates this from simply deleting sensitive text. Because the mapping stays local, the reversibility doesn't require sending anything anywhere.

What it detects

The tool advertises 30+ patterns across 13 languages. From the detection categories and examples on the page:

Optional pattern packs extend coverage to Crypto (BTC, ETH, keys), Kubernetes, Terraform, Comms (Slack, Teams, Twilio), and Location & Coordinates.

Controls that matter in practice

• Custom words to redact — a comma-separated list that is always redacted regardless of pattern, useful for project names or internal codenames.
• Allowlist — values that should never be redacted, so common words or public identifiers don't get masked by mistake.
• Custom regex patterns — add your own detection rules, with a case-insensitive option.
• Saved presets — save, load, delete, export, and import your configuration.
• Redact selection — anonymize only a highlighted portion rather than the whole input.

Where you can run it

• Live tool in the browser (the primary interface).
• Browser extension — auto-anonymizes on paste into ChatGPT, Claude, Gemini and others; available for Chrome and as a Firefox add-on.
• VS Code extension — anonymize selections without leaving the editor.
• Python package — pip install privatiser.

When it's the right choice — and when it isn't

Privatiser is a good fit if your main concern is pasting sensitive text into a hosted AI service and you want a reversible, structure-preserving redaction that never uploads your data. The local-processing claim is the central selling point, and the deanonymize step means you don't lose the ability to map the AI's answer back onto real values.

It's less suited if you need server-side auditing, team-shared mappings, or centralized policy enforcement — the design is deliberately local and single-machine. The page also doesn't state pricing beyond a "PRO" label on the settings panel and a "Pricing" link, so check the site directly for what's free versus paid before relying on it for a workflow.