AI Receptionist for Medical Clinic
Deployed an AI voice receptionist handling 200+ calls/day for appointment booking, rescheduling, and patient FAQs — running 24/7 without missing a call.
The Challenge
A busy multi-doctor dental clinic was missing 60–80 calls per day during peak hours because the front desk couldn't handle the volume. Missed calls meant missed bookings — estimated at ₹4–5 lakh per month in lost revenue. After-hours calls went to voicemail and were rarely returned promptly.
What We Built
We deployed an AI voice receptionist powered by Twilio and a custom Python backend. The AI handles the full booking conversation: greets callers, identifies the type of appointment needed, checks real-time availability via the clinic management system API, books or reschedules appointments, sends confirmation SMS, and answers common patient questions. It escalates to a human only when clinically necessary.
How It Works
The clinic's front desk team was talented but undersized for the call volume. During morning rush hours (9–11am), the phone would ring continuously. Patients who couldn't get through called competitors. The clinic estimated they were losing 15–20 bookings per day to missed calls alone.
We integrated Twilio's programmable voice with a Python-based conversation engine. When a patient calls, the AI answers within one ring. It identifies the patient's intent — new appointment, reschedule, cancellation, or FAQ — and navigates the appropriate flow.
For bookings, the system calls the clinic's management software API in real time, pulls available slots, and offers them to the patient conversationally. Once a slot is chosen, it creates the booking in the system and sends a confirmation SMS — all within the same phone call.
Patient FAQs (insurance accepted, clinic hours, parking, what to bring for first appointments) are handled from a knowledge base without any API call. The AI escalates to a human only for clinical questions or upset patients — roughly 18% of calls.
Since deployment, zero calls are missed. The front desk team now focuses entirely on in-clinic patient care. The clinic reports the system paid for itself within the first month through recovered bookings.
