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🚨 A dental clinic was losing patients every single day.
Not because of bad service. Not because of high prices.
Because nobody was replying to messages.
Patients messaged on WhatsApp, Messenger, SMS… And waited. And waited. And left.
The clinic owner contacted me with one simple ask:
“I can’t hire someone to reply 24/7. Can you help?”
So, I built them an AI receptionist that never sleeps. 👇
Here’s exactly what it does:
✅ Omnichannel Support: Instantly replies to patients on WhatsApp, Facebook Messenger & SMS — all from one system.
✅ Human-like AI: Google Gemini AI understands the message, detects intent, and replies naturally.
✅ Smart FAQ Handler: Answers questions about services, pricing & clinic hours by pulling live data from Google Sheets.
✅ Automated Booking: Checks availability, blocks double-bookings, and confirms only after saving to the sheet.
✅ Instant Alerts: Notifies the clinic owner instantly via Gmail + Telegram on every new booking.
✅ Smart Reminders: Sends automated email reminders — 2 hours and 1 hour before the appointment.
✅ No-Show Recovery: Detects missed appointments and automatically sends a polite rescheduling email after 12 hours.
The Tech Stack 🛠️:
⚙️ Make.com — Automation backbone
🧠 Google Gemini 2.0 Flash — AI brain
📊 Google Sheets — Live clinic database
💬 Green API — WhatsApp integration
📱 Facebook Messenger API & Twilio — Chat & SMS
✉️ Brevo — Email reminders
📢 Telegram Bot — Owner notifications
💾 Make.com DataStore — Conversation memory per patient
The Result? 📈
Every patient gets an instant, intelligent reply — 24/7. No missed bookings. No forgotten appointments. No manual follow-ups.
The clinic owner now wakes up to confirmed appointments already in the sheet with zero manual effort.
This is what I build for businesses. If you’re still replying manually and losing leads while you sleep — DM me. Let’s fix that. 👇
#MakeAutomation #AIAutomation #NoCode #Makecom #GeminiAI #WhatsAppAutomation #BusinessAutomation #AIReceptionist #FreelanceAutomation #Upwork #Fiverr
For the Sheets booking step, I'd test two patients requesting the same slot at the same moment through different channels. How do you prevent both Make runs from reading it as free before either writes the booking?
Great question! For a basic MVP setup, I handle that with a quick Apps Script lock or by checking availability right before the write step. For high-scale production, moving to a database with unique constraints solves it natively!
Nice build, and very close to a WhatsApp assistant I just built for a dental-clinic use case on the WhatsApp Cloud API. Two things mattered a lot in testing: when a patient asks for a person, the bot has to go completely quiet for that chat until the owner hands it back, and the...
Spot on! I used Gemini 3.5 Flash for intent detection on phrases like 'talk to a person', paired with a Make DataStore flag (human_takeover = true) to completely pause the bot for that specific chat until the owner manually resets it. As for languages, since clinics often handle...
Smart setup. The one thing I'd stress-test is multi-turn: a single-message intent model can miss "ok fine, just get me a human" after three bot replies, because the trigger is split across turns. I ended up checking the last couple of messages together, not just the newest one....
Great point on multi-turn context! To handle that, I pass a rolling history (a window of the last few messages) into Gemini 3.5 Flash during the intent check, so it catches phrases like 'ok fine, just get me a human' even when split across turns. And yes—the DataStore flag...
The detail I like most is the order of operations — it confirms only after saving to the sheet. That's how you avoid phantom bookings where the patient thinks they're in and the clinic has no record. The no-show recovery after 12 hours is smart too, most builds stop at the...
Great catch! For clinical or out-of-scope questions, the system detects the intent using Gemini's fallback triggers. Instead of giving medical advice, it pauses or triggers an instant alert to the clinic owner via Telegram with the conversation context, so the doctor or...
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Same screen, two modes. Which one would you work in all day? 👀
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Keeping the research plan and cited results side by side is a useful way to make the agent’s work easier to inspect. I’d lean toward light mode for reading the table in daylight. How do you distinguish a verified source from one that still needs review?
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Try it live: https://lab.behzad.me/agent-mew/
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Approval cards for anything that leaves the Mac is the right line to draw. Does the card show the full email before you tap OK, or a short summary? I'd lean toward full text for anything going to another person.