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Use case

Redact PII before sending text to an LLM

Every prompt you send to a hosted model leaves your boundary. If that prompt contains a customer's address or card number, you have just made a data transfer to a processor that your privacy notice probably does not cover. Redactly sits in front of the model call and replaces the identifying spans with stable type labels.

Try it on the live API No signup. 2,000 characters, 20 runs per 10 minutes.
Output appears here.

What this gives you

  • Redact first, then send. The model sees [identity.person_name] and [contact.email] instead of the real values, and can still reason about the sentence.
  • Labels are type-based rather than random tokens, so the model keeps the semantics it needs to answer.
  • Nothing is stored: the request is redacted in memory and the response is returned synchronously.
  • If you need the original values back, keep your own mapping — Redactly's output is irreversible by design.

Request

curl -X POST https://api.bitbanger.in/v1/redact \
  -H "X-API-Key: rdct_your_key_here" \
  -H "Content-Type: application/json" \
  -d '{"text": "Summarise the complaint from Jane Doe at jane.doe@example.com about card 4242 4242 4242 4242."}'

Questions

Does this work with OpenAI, Anthropic, or any other provider?

Yes. Redactly is provider-neutral: it redacts the string before you build the request, so it works with any chat or completion API, including self-hosted models.

Can I restore the original values after the model responds?

Not from Redactly's output, which is irreversible. Keep your own token-to-value map on your side if you need to rehydrate.

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