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Redact email addresses from text, JSON, and CSV

Email addresses are the most common PII in support tickets, logs, and exported datasets, and the most common cause of accidental disclosure. Redactly replaces them with a type label while leaving the surrounding text untouched.

How Redactly detects email addresses

• Matched by a format regex that runs independently of the model, so an address is caught even when the surrounding sentence gives no context.
• The whole address is the span — no fragments such as the domain alone being reported.
• If a token also resembles a URL, the email boundary wins because the address match is authoritative.

Why redact email addresses?

A single leaked address list is enough to trigger a GDPR personal-data breach notification.

Example 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": "Escalation contact: priya.raman@northwind-example.com, ticket #4412.", "style": "replace"}'

Every hit in the response carries entity, text, start, and end. The offsets index into the text you sent, so you can apply the redactions to your own copy of the document. The full response schema is in the API reference.

Questions

Related entity types

• Phone numbersRedact phone numbers in national and international formats from text, JSON, and CSV. Model-gated, so dates and ID numbers are not mistaken for numbers.
• UsernamesRedact handles and account usernames from transcripts, exports, and community data.
• Person namesRedact personal names from free text, including partial names the model only half-captures.