Review Management
A job closes. The agent sees the field flip on the record you pointed it at, waits the window you set, and sends that customer a private check-in and the public review request — the same message to everyone inside the trigger, whether or not you expect them to be nice about it. When someone answers unhappy, it reaches you before it reaches your review page. When a review lands, the agent drafts a reply into a queue. It never posts on its own.
Yours outright — no required subscription.
Every agent is built for your business — your systems, your approval chain, your way of working. We scope it on the call.
If this sounds too technical, don't worry. We take care of everything for you.
- Private VPS deployment. This agent runs on a server that belongs to you, not a shared cloud tenant. Private VPN, firewall, and encryption are configured before it ever messages a customer of yours.
- A technician agent alongside it. Every hire ships as a pair: the Review Management Agent that asks, listens, and drafts, and a VPS-technician agent that lives on the same box and keeps it healthy — patched, backed up, monitored. You're not hiring one thing, you're hiring a small team of two.
- A trigger wired to what actually means done. Not "invoice sent," not "label printed" — the field in your own system that genuinely marks the work finished, plus the delay you want after it. Punch lists, warranty callbacks, reschedules, and accounts you never want touched are excluded during setup, before anything sends.
- The private check-in and the public ask, sent together. Both go to every customer inside the trigger window. The check-in gives you a head start on a problem; it is not a filter that decides who is worthy of being asked.
- A reply queue instead of a posting bot. New reviews land in a queue with a drafted response beside each one, written in your voice and against your history with that customer. You edit, you approve, you post.
- A live walkthrough of both agents, followed by 14 days of priority support to tune the trigger and the wording against your real job mix.
- You own everything — the server, the agent, the code it runs on.
Not sure it fits? Check fit in 90 seconds in the free assessment chat.
Who this is for
- You're running a 15-person contracting or home-services shop where the crew closes eight to twelve jobs a day, the review link lives in a sticky note, and requests only go out when the office manager gets a slow Friday.
- You do enough order volume that the confirmation is automatic but the review request is not, and the only feedback you ever hear comes from the customers angry enough to find your contact form.
- You run a clinic or a professional practice where a bad review sits up for a week because nobody wants to be the one who answers it wrong, and the last time someone did answer, you called your attorney about whether the reply said too much.
- You're a 4.2 against a 4.8 down the road and you know for a fact your work is better — the difference is that they ask everyone and you ask whoever comes to mind.
How it earns trust
The failure mode of AI in review management isn't that it sends an awkward message — it's that you can't tell who it asked, who it skipped, or why. This agent is built around the opposite bet: every ask, every check-in, and every drafted reply leaves a record you can read.
Every send stamped to the job
Which job or order triggered it, which field flipped and when, which channel it went out on, which number or address, and the exact text that was sent. When a customer says nobody ever asked them, you open the record and see.
An ask log that is deliberately complete
Not a filtered view. You can pull every customer inside a trigger window and confirm the request went to all of them — the artifact that shows you weren't picking favorites, if anyone ever asks you to prove it.
The draft stored beside what you posted
Each drafted reply is kept next to the review it answers and next to the version a human actually published, so you can read what the agent wrote against what you sent and tighten it.
Asks sent, private check-ins returned, public reviews landed — the weekly count turns your ask-to-review ratio from a guess into a number, though what that number should be depends entirely on your customer mix, and we'd rather size it with you on the call than promise one up front.
Pairs well with
These share a workflow with this role. Tick any to add them to your setup.
We do great work and we've got eleven reviews. Will this actually change that?
The gap is almost never quality, it's volume of asks. Right now you ask the customers someone happens to remember; this asks every customer inside a trigger you define, the same week the work finished. What it can't do is make anyone write one — a share of people will always ignore the request, and the honest number to watch is asks-to-reviews over a few months, not the first fortnight.
Sarah's supposed to send those out, but she's covering the phones.
That's the part this replaces. The send fires off the record, not off someone's Friday afternoon, so a busy month and a slow month produce the same ask rate. Sarah still owns the exceptions — the accounts she flags as off-limits, and the replies she approves before they post. Typically live in about seven days from kickoff.
Can it just ask the customers we know are happy?
No, and we'd turn down that build. Choosing who gets asked based on how you expect them to answer is review gating, which platform policy and the FTC both reach, and an agent doing it quietly does it at scale. Everyone inside the trigger you define gets the same ask. It also never offers a discount, credit, or waived fee in exchange for a review, and it never tries to make an existing review go away — no disputing, no flagging, no asking a customer to take one down. Anyone who has opted out, or anyone you've flagged as in a dispute, it does not contact at all.
Every time I answer an angry one I make it worse.
Which is why the draft is a draft. The agent writes a starting point beside the review and stops there; nothing posts publicly without a human approving it, and that goes double for anything negative. It also has no reliable sense of which detail is protected — that this person is your patient, when they came in, what was done. If you're in a regulated field, treat every draft as a first pass a person who knows the rules has to rewrite, not as a reply that's ready to send.
That review's been up three weeks and I still haven't answered it.
A drafted reply is waiting the same day the review appears, so the delay becomes a two-minute approval instead of a group text at 9pm. Be aware of the reach limit: posting programmatically to some review platforms requires a manual approval from them, not a setting, and at least one major platform prohibits soliciting reviews at all and filters the solicited ones. Realistically the agent asks, listens, and drafts; on some platforms a human still pastes the reply, and some we'll tell you to leave alone.
What's covered under the $1,997 setup, and what isn't?
One company, one system of record, one approval chain. You own the server, the code, and the keys; we keep the SOP playbook we built it from. Multiple locations with separate profiles, or several systems that each think they know when a job is done, get scoped on the free 15-minute call rather than priced off a page.
Hiring more than one? A department on tap — the subscription puts a build team behind every request, agent after agent.