A 24/7 AI assistant that answers patients across 5 Mumbai clinics — in Hindi, Marathi, English, and any other language a patient happens to write in. It hasn't slept a night since it went live.
A senior pulmonologist with 37+ years of practice across five clinics in Mumbai. Patients across Ghatkopar, Kurla, Chembur, and the surrounding areas were messaging the practice WhatsApp at all hours — asking the same questions about timings, addresses, fees, services, and appointments.
A receptionist was answering them during the day. At night, on holidays, and during consultation hours, messages piled up — and lost patients along with them. Hiring an after-hours receptionist costs ₹15,000–25,000 a month. That receptionist still sleeps, still speaks one language at a time, still can't be in five places.
We didn't want a chatbot. We wanted something patients could trust at 2am, in their own language, without anyone on staff lifting a finger. — The clinic's request, paraphrased
Eight specific behaviours, all derived from real patient conversations during the first weeks of testing.
Taken from the live deployment. Same system runs for any clinic — only the names, languages, and locations change.
Nothing exotic. Just careful choices, each one aimed at making the conversation feel human.
The clinic's existing WhatsApp number is registered as a verified business account on Meta's official Cloud API. Free service conversations cover normal volume; per-conversation costs are folded into the monthly engagement.
The system's behaviour is governed by a long, carefully written prompt that captures the doctor's tone, the practice's services, every clinic's address and timings, and the explicit safety rules. It was rewritten more than a dozen times during testing.
Patient messages are interpreted and replied to by frontier multilingual models — fluent in every major Indian language. The reply is in the same language the patient wrote in, automatically.
Every conversation is stored — searchable in the dashboard, exportable on request. Nothing shared with any third party. If the clinic ever leaves, the data leaves with them.
When a booking is collected, the clinic team gets a formatted WhatsApp message with the patient's name, issue, preferred time, and the source clinic — within a couple of seconds.
The assistant has been in continuous service since launch. It handles the bulk of repetitive WhatsApp traffic — addresses, timings, services, fees — and routes every real booking to the clinic team with the patient's name, issue, and preferred time already parsed.
The doctor's staff still handle the conversations that matter. The assistant handles the ones that used to get lost.
Out of professional courtesy and patient confidentiality, this case study refers to the doctor only by specialty and experience. A direct introduction is available on request — message the studio.
Two sentences about your clinic is enough to start. An honest answer comes back within a working day on whether it's a fit.