Trust is the barrier
41%
Case study
Five specialised AI agents. One patient journey. From first "Hello" to post-treatment recovery — in Hinglish, with full human oversight, deployed in 3 days.
Assets
Images are carried over from the live page and framed inside the current Peach design system.
Highlights
Building AI for a high-trust, nuanced vertical?
41%
Patient queries handled entirely by AI
Better appointment show-up rate with ₹49 token
3days
To build and deploy each new agent - no developer
When a man is nervous about a sensitive health issue, a robotic flow feels cold. He sees a menu, feels like a ticket number, and leaves. The clinical friction is the conversion killer — not the product, not the price.
Details
Men reaching out to Raaz are already anxious. Any moment of friction — a confusing menu, a generic question, a delayed reply — breaks the fragile trust needed to continue.
Triage, scheduling, anxiety management, payment nudging, and post-care follow-up are four completely different jobs. A single agent trained to do all of them does none of them well.
Patients communicate in Hinglish — a natural Hindi-English mix. A bot that does not understand Devanagari script, local slang, or even a rushed typo loses the patient immediately.
Hiring enough human agents for 24/7 empathetic support is expensive and impossible to scale. But pure automation without warmth is worse than no automation at all.
Instead of one bot trying to do everything, Raaz built a crew. Each agent hands off to the next when their role is done. Every agent was built in plain English — no code, no flowcharts. A junior intern manages the flows.
The Empath — First contact & triage
+58% conversion
What it does
Greets every user as "Sir." Never asks for their name straight away. Communicates in natural Hinglish using Devanagari script. Identifies whether the user has a problem, then asks about their situation — gently, without judgment.
Why it works
Removing the judgment barrier increased lead-to-booking conversion by 58% vs the previous static menu flow. Patients feel safe — not processed.
Plain English instruction used
"You are a helpful friend named Kundan. Assist men with PE and ED only. Communicate naturally in Hindi using Devanagari script. Never ask for their name immediately — keep them anonymous until they feel safe."
Appointment booking
Slot to confirm <2 min
Once the patient admits they have a problem, this agent takes over. Connects to Zoho CRM. Offers three specific 1-hour slots in AM/PM format to cut decision fatigue. Confirms without asking for re-confirmation. Tells the patient to save the doctor's number as "Raaz Incoming."
Specific slot options remove the paralysis of open-ended scheduling. The "save as Raaz Incoming" instruction means patients recognise the call and pick up. Slot to booking under 2 minutes.
FAQ & pre-appointment anxiety
Reduces cancellations
Between booking and the appointment, patients get nervous and cancel. This agent manages the anxiety window. Answers safety and privacy questions by reading from an uploaded FAQ PDF. Handles Hinglish typos — "binaries" instead of "bimari" — without breaking.
A patient in a hurry makes typos. The agent understands intent, not just spelling. Pre-appointment cancellations dropped because patients got answers fast — without waiting for a human.
How the FAQ was added
The team uploaded a PDF of their FAQs into Peach. The agent reads the file to answer questions. Adding new topics takes minutes — upload a new PDF and the agent handles it the same day.
Order & payment
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