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Version: 2.0.0

PII Redaction in Corpus

What is PII Redaction?​

Personally Identifiable Information (PII) Redaction refers to the process of identifying and obscuring sensitive information in documents or data that could be used to identify an individual. This includes information such as names, addresses, phone numbers, social security numbers, email addresses, and any other data that can uniquely identify a person.

PII Redaction in Corpus​

With the introduction of PII Redaction in Corpus Indexing Settings, users can ensure that sensitive information within their documents is protected and not accessible to unauthorized entities. This feature is particularly useful when sharing knowledge across multiple assistants and projects, where privacy and data protection are critical.

How PII Redaction Works​

When creating a new Corpus in Ejento AI, users now have the option to enable PII Redaction.

  1. Document Analysis: Once a document is uploaded to the Corpus, It is automatically scanned for any PII Content.
  2. Redaction Process: Identified PII is then redacted, meaning it is either masked or replaced with placeholders to prevent exposure of sensitive information.
  3. Assistant Interaction: When assistants access the Corpus, they interact with the redacted version of the documents, ensuring that PII remains protected while still allowing assistants to use the non-sensitive information for generating responses.

Benefits of PII Redaction in Ejento AI​

  • Enhanced Privacy: By redacting PII, organizations can safeguard sensitive personal information, complying with privacy regulations.
  • Secure Collaboration: Teams can share documents across multiple assistants without the risk of exposing sensitive data, fostering a secure environment for collaboration.
  • Compliance and Trust: Implementing PII redaction demonstrates a commitment to data protection, building trust with clients and stakeholders.

By incorporating PII Redaction into the Corpus feature, Ejento AI provides a robust solution for managing sensitive information while maintaining the utility and accessibility of shared knowledge across assistants.