Purview Communication Compliance
Atlanta, USA (United States of America)
Last updated: 2026-07-27
References
Communication Compliance helps you detect, capture, and act on inappropriate messages that can lead to data-security or compliance incidents. It evaluates text and image messages across Microsoft and third-party channels for potential business-conduct and regulatory violations, with privacy controls built in.
Source: Communication Compliance overview.
Why it matters
Detecting harassment, threats, and inappropriate sharing is part of compliance with internal policy and regulation. Communication Compliance uses machine learning classifiers and keyword matching, with human review before any action.
| Without Communication Compliance | With the solution |
|---|---|
| Policy violations in messages go undetected | Classifiers flag potential violations for review |
| Reviews risk bias from visible identities | Pseudonymization minimizes investigation bias |
| One role holds too much power | Roles separate policy authoring from review |
| Actions are ad hoc | Remediation and audit follow a defined workflow |
Value in one line: it surfaces potentially harmful or non-compliant messages for human review while protecting privacy and separating duties.
Policy templates
Built-in templates cover business conduct, such as discrimination, profanity, threats, and targeted harassment, and regulatory compliance, such as money laundering, regulatory collusion, and unauthorized disclosure. Combine classifiers with keyword, sensitive-information, and scope conditions to tune them.
Configure responsibly
- Learn the solution and verify licensing.
- Enable the audit log and configure prerequisites.
- Assign least-privilege administrator, investigator, and reviewer roles.
- Create policies with the channels, classifiers, and conditions you need.
- Investigate and remediate matches with human review and recorded outcomes.
Verify and operate
- Confirm the audit log is enabled and the chosen channels are actually monitored.
- Combine classifiers with keyword, sensitive-information, and scope conditions to reduce false positives.
- Keep human review before any action, and use the misclassification feedback loop to improve classifiers over time.
- Review reviewer decisions and remediation outcomes, and preserve them as evidence.
Business example
A policy monitors Teams and Exchange for harassing language. A reviewer sees a pseudonymized match, confirms the violation, removes the message, and notifies the sender, while the decision and action are recorded and the identities stay protected unless an authorized process requires them.