Asks at the point a patient is most likely to say yes, suppresses the visits where asking is wrong, and routes anything unhappy to the practice.
An AI agent for dental review requests handles the gap between how good a practice is and how good it looks online. Dental practices are unusually poorly represented by their review counts, because the moments when a patient is most grateful are not moments anybody remembers to ask about, and the front desk is busy at exactly the point the patient is leaving. The agent asks after the right visits, at the right interval, once. The more important half is what it does not do: it suppresses the request where asking would be wrong — a difficult appointment, a complaint on file, an unresolved billing question — and it routes a patient who responds unhappily to the practice rather than pushing them toward a public review. Built on Agentplace: the agent runs on its own page, so a visitor finishes the whole request in the conversation.
Asks after the right visits and suppresses the wrong ones.
Asks after visit types where a review is appropriate
Waits the interval that suits the treatment before asking
Suppresses the request where a complaint or issue is on file
Asks once, with one reminder at most
Routes an unhappy response to the practice, not to a review site
Never asks a patient to write anything specific
Any system can send a review request after every appointment, and doing so is how practices end up asking a patient with an unresolved billing dispute to rate them publicly. The judgment that matters is suppression — and it is judgment a front desk exercises naturally and an unconditional automation does not. Getting this right means the requests that do go out land on patients who had a good visit, at a point where they still remember it, which produces both more reviews and better ones. Routing dissatisfaction to a person rather than to a review page is not about hiding it: a patient who says privately that something went wrong gives the practice a chance to fix it, and practices that handle that well often end up with a review anyway. What must not happen is an automated system pushing an unhappy patient toward a public form.
Wait for the right visit, check suppression, ask once.
Some treatments are worth asking about the next day; others need the result to settle first.
A complaint, a billing dispute or a difficult appointment stops the request going out at all.
One ask, at most one reminder; anything unhappy goes to the practice rather than onward.
The request that did not go out.
Scenario: a practice with strong clinical outcomes had 44 reviews in six years and had recently asked a patient with an unresolved billing query to review them, which went badly. The agent begins asking after appropriate visits. In its first month it sends 71 requests and suppresses 9 — five where a billing question was open, three after appointments the clinician had flagged as difficult, and one patient who had complained the previous quarter. Twenty-three reviews are left. Two patients reply unhappily rather than reviewing: one about waiting time, one about a crown that felt high. Neither is pushed toward a public form; both are routed to the practice the same day, and the crown is adjusted that week. That patient later leaves a five-star review unprompted, which is a better outcome than the one an unconditional system would have produced.
Anybody whose review count does not match their dentistry.
Your online reputation is not what your clinical work deserves.
Asking after every visit is how you get a bad one.
A patient with an issue should reach you, not a review site.
You are busiest exactly when the patient is leaving.
New patients choose on review count and recency.
You have the outcomes and none of the visible proof.
Where the visit is recorded and where the answer goes.
Holds visit types, suppression flags and request history.
Sends the request on the channel patients answer.
Reaches patients who prefer email.
Receives the review the patient chooses to leave.
Routes an unhappy response to the practice the same day.
Reports request, response and suppression rates.
The moments that decide whether asking works.
Questions about asking dental patients for reviews.
An AI agent for dental review requests asks after appropriate visits at an interval that suits the treatment, suppresses the request where a complaint or billing issue is on file, asks once, and routes an unhappy response to the practice rather than toward a public review.
Routing them to a person is. What is not legitimate is offering a public form only to people who say they are happy — the difference is that everyone gets asked and everyone can review; the unhappy ones also get a call.
Anything with an open complaint or billing dispute, appointments the clinician flagged, and patients asked recently. Suppression is the part that requires thought; sending is the easy half.
It depends on the treatment. Some are best the next day while the relief is fresh; others need the result to settle before a patient can judge it. A single fixed delay serves neither well.
Once, with at most one reminder. Dental patients are asked for reviews by everyone; a third request converts almost nobody and costs goodwill.
No. Beyond looking manipulative, a review that reads as scripted is worth less than a short honest one, and platforms are increasingly good at spotting the pattern.
Review count and recency, and separately the suppression rate. A suppression rate of zero means the checks are not working, not that every visit went perfectly.
It runs on Agentplace. Agentplace is an AI agent platform where the agent gets its own page, talks to your visitors there, and carries the request through to the end instead of handing it to a form. You can open this template and change any step before you publish it.
Asks at the point a patient is most likely to say yes, suppresses the visits where asking is wrong, and routes anything unhappy to the practice. Open it in Agentplace and change any step before you publish.