Stripping personally identifiable information before sending to a model.
1 min readupdated 2026-07-04
/ quick answer
PII redaction detects names, emails, phone numbers, IDs and replaces them with tokens before the payload leaves your infrastructure. Reversed on the response for the end user. Stripping personally identifiable information before sending to a model.
Stripping personally identifiable information before sending to a model. PII redaction detects names, emails, phone numbers, IDs and replaces them with tokens before the payload leaves your infrastructure. Reversed on the response for the end user. In practice: A customer-support pipeline replaces 'John (john@acme.com)' with '[USER_1] ([EMAIL_1])' pre-inference. This dictionary node is part of the Onexial knowledge graph and links to related concepts, workflows and tools below.
Definition
PII redaction detects names, emails, phone numbers, IDs and replaces them with tokens before the payload leaves your infrastructure. Reversed on the response for the end user.
Example
A customer-support pipeline replaces 'John (john@acme.com)' with '[USER_1] ([EMAIL_1])' pre-inference.
PII redaction detects names, emails, phone numbers, IDs and replaces them with tokens before the payload leaves your infrastructure. Reversed on the response for the end user.
What is an example of PII Redaction?
A customer-support pipeline replaces 'John (john@acme.com)' with '[USER_1] ([EMAIL_1])' pre-inference.
Why does PII Redaction matter for AI and automation?
Stripping personally identifiable information before sending to a model. It connects to the workflows, prompts and tool stacks linked on this page, so you can move from definition to execution without leaving Onexial.