The problem it helps with
Repetitive customer communication quietly eats your team's day. AI Reputation Manager takes the routine parts off your plate.
How AI Reputation Manager works
Scroll through a typical interaction. Illustrative example — configured around your business, not a live AI integration unless connected.
Business completes service
Your team finishes delivering the service to the customer.
Feedback request triggered
A review request is automatically queued after completion.
Customer gives feedback
The customer receives the request and shares their experience.
Review link accessed
Happy customers can access your public review link when they're ready.
Feedback logged
Relevant feedback is recorded so it stays organized.
Staff notified
You're alerted to new feedback so you can respond or thank the customer.
Features & practical use cases
Reviews AI
Requests and helps organize customer feedback.
Review request workflows
Triggers feedback requests after completed services.
Email & configured SMS
Sends requests through the channels you've set up.
Feedback & owner alerts
Logs feedback and notifies you when it comes in.
Typical use cases
- Requesting a review after a completed service
- Sending a feedback link to a happy customer
- Logging feedback so it's organized
- Alerting you to a new or negative review
Advantages & limitations
Honest limitations
- Never promises five-star reviews or fabricates endorsements.
- Public replies require your approval.
- Negative or sensitive feedback is handed to a person.
Underlying AI capabilities
AI Reputation Manager draws on a connected set of AI capabilities managed by RRelevate — not a single isolated model.
Package availability
Available on AI Growth Team and Enterprise.
Availability and billing depend on your agreed RRelevate plan. Applicable AI usage is billed according to your plan and current usage terms.
Human handoff
- Negative reviews needing a response
- Public replies requiring approval
- Reputation-sensitive situations
What you receive
- New review submitted
- Negative feedback received
- Review request sent