A bot that answers every review about your venue fast, sharp and never boilerplate
The reply everybody sees beats the fix nobody sees
of diners read reviews before they pick a place
also read what the business wrote BACK
Source: Adpass, roundup of consumer behavior research, 2026
A one-star review sitting there with nothing under it gets read by thousands of people, and every one of them lands on the same thought: “nobody’s minding the store, nobody cares, let’s eat somewhere else.”
So when a bad one comes in, you have to answer first — own it, sound like a person, say what you’re doing about it. Actually chasing down the problem the guest hit is step two.
Answerolog drops the review straight into your DMs with 3 ready replies, each in a different tone
The bot finds your listing and learns how your place talks
You answer a couple of questions up front. That’s the whole setup.
It watches the review sites and sends you the review plus 3 replies sharp enough to come from a very good copywriter
You copy it. You post it.
Yes, you post it yourself — the bot takes the busywork off your plate, not the responsibility.
burned on wordsmithing at 11pm after twelve hours on your feet
give the job to anyone on the team without lying awake wondering what they just posted
Reads every review at once: what people rave about, what keeps coming up in complaints, which days and hours things go sideways
sauce
pickup
wrap
Urgent: check the recipe
Second in line
Random
Tuned on 500,000 real reviews
Claude writes by default. Swap in any of the others whenever you feel like it — two taps in settings.
Here’s everything the 2GIS AI will write for you
“Hi there! Thank you so much, feedback like this really makes our day!!! Hope to see you again 🤗”
“Thank you for stopping by and for the great rating! We look forward to serving you again!”
Here’s what Answerolog hands you instead
The quesabirria here is unreal, and the consommé actually tastes like something.
Glad we’re finally getting spots like this on this side of town instead of another chain.
The consommé is the part we fight over in the back too 🍜 Thanks for the shout — and for the bit about the neighborhood, that one landed. Come hang out any time, we’re not going anywhere.
Not the same since the menu change.
The quesabirria barely has cheese in it now, it’s mostly sauce, and there’s less of that than there used to be.
A quesabirria with no queso is, we admit, a branding problem. Your note about the filling since the menu change is written down and we’re on it this week. Text us at the number on our listing — we’d like to make this one right.
Ten minutes past the time they quoted me
and then handed me a taco burnt on one side with raw onion instead of grilled.
Danielle, thank you for writing this up, and you’re right on both counts: ten minutes over the quote is on us, and nothing should ever leave the window burnt. We’re pulling the ticket times to see what happened. Could you tell us the day and roughly the hour you came in? Our number is on the listing — call or text and we’ll square this with you directly.
Four honest reasons this is worth paying for
One small, never-ending headache goes away: what to say back, and how to word it
The four best AI models in the world write for you, and you’re not paying for four subscriptions
It’s tuned on an archive of 500,000 real reviews across nine kinds of venue, not on somebody’s idea of what people write
Reads every review: what people complain about, what they praise — and sends a weekly breakdown. Helps you tell a real problem from a one-off
Questions
What’s the catch?
There’s one, and it’s the only one. Reviews don’t land the second they’re posted: the review sites sit on their data and hand nobody an open API, so it takes minutes to a few hours: 2GIS arrives almost at once, Yandex is slower. For this job that’s fine — most places take a day or two to answer anything at all.
And even that has a way around it. Beat the bot to a review? Screenshot it straight into the chat. The bot reads the text off the image and gives you three replies on the spot, no waiting. That one won’t come around twice later, either — it recognizes the review by its text.
I don’t run a restaurant — does it fit?
It fits any venue that gets reviews on 2GIS or Yandex Maps: a shop, a beauty salon, a car service, a hotel, a gym, a driving school, a pickup point. The bot works out the niche itself from the listing category and answers in its words — a car service about turnaround and intake, a shop about stock and the till, a hotel about the room and check-in. One exception: medicine and pharmacies. A public reply from a clinic would confirm that a person came to them, and that is medical confidentiality, so the bot does not serve those.
Do you need access to my business listing?
No — and not on any plan, ever. Name and address is all it takes: the bot finds the listing itself and shows it to you to confirm. We never ask for logins or passwords.
Who actually posts the reply?
You do. The bot writes it, you copy it with one tap and paste it on the site. Nothing ever goes out under your name without you.
What if none of the three sound right?
Rewrite as much of it as you want — it’s plain text, it’s yours. Or switch the AI in settings: Claude, GPT, Gemini and Grok have noticeably different handwriting under exactly the same rules.
I’ve got more than one location
Each one connects separately: every location has its own listing and its own stream of reviews. Every next one costs less — 20% off from the second, 40% off from the sixth. One payment covers them all on one date, and each gets its own weekly digest.
Can you get bad reviews taken down?
No. Only the site can pull a review, and only if it breaks their rules. What we do is help you answer — and the answer is what the next guest actually reads.
What data is the system trained on?
It’s an open archive of location reviews: 500,000 records about real venues with categories — cafés and bars, shops, hotels, salons, car services, gyms, banyas, museums, workshops. We counted what people complain about in each niche separately: staff in shops (11.6% of complaints), cleanliness in hotels (14.4%), waiting and a surprise bill at car services. The bot’s own rules are checked against the same reviews: 42,851 one- and two-star reviews show where a reply slips into an argument or promises more than you can deliver. Medical venues and pharmacies are excluded from the archive — we don’t serve them.
Which sites do the reviews come from?
2GIS, Flamp and Yandex Maps. Flamp needs no separate setup: it belongs to 2GIS and they share the same reviews — at one venue we measured, 85 of 128 reviews came from there. Google goes in once there are venues outside Russia.
How many reviews does a venue get in a month?
We counted on live listings: 2GIS brings a venue 12 to 56 reviews a month, Yandex Maps two or three. On the accumulated pile the gap is starker still — the venue we tuned the collector on has 709 reviews on 2GIS against 38 on Yandex.
Do good reviews need a reply too?
Yes, and they’re the majority. Across the 472,297 reviews of venues we serve, only 13.4% carry a low rating — the rest are fours and fives. Silence under a thank-you reads exactly like silence under a complaint, so the bot sends three options for praise as well.
Are these auto-replies? Does the bot post them itself?
No. There’s no auto-posting and none is planned: the bot prepares three options, you post the one you pick — one tap to copy. That’s also why it needs no access to your account on the review site.