Zeelab Pharmacy sells WHO-approved generic medicines at up to 90% off branded prices through 200+ partner stores across India. Their value proposition was compelling, quality generics at radical affordability. But their ordering process was killing growth: every medicine order required phone calls, manual prescription collection, back-and-forth address coordination, and constant availability that small teams couldn't sustain.
Agentific built a WhatsApp-native ordering system that handles the complete journey, from medicine browsing to delivery tracking, without requiring the team to be online. The system recognizes new vs. returning customers, adapts to their needs with separate optimized paths, operates in both English and Hindi with instant switching, and recovers abandoned carts automatically.
The Result: Pharmacy team freed from routine order-taking to focus on complex medical questions and high-value customer relationships.
Zeelab Pharmacy operates as a direct-to-consumer generic medicine platform across India. Founded by Rohit Mukul in 2019, the company focuses on providing high-quality, WHO-approved generic medications from GMP-certified manufacturing plants at prices up to 90% lower than branded alternatives
Rather than building their own retail footprint, Zeelab partners with 200+ existing pharmacy stores across India, creating a distributed network that brings affordable essential medications directly to consumers without the overhead of traditional pharmacy chains.
The Challenge
Zeelab's team was drowning in routine work. Every medicine order followed the same manual pattern:
The breaking point: Turning away orders because the team couldn't respond fast enough during peak hours. More customers meant more manual work, more hiring, thinner margins
The core tensions:
Availability gap - No service outside business hours meant lost orders from customers who searched for medicines at night
Language barrier - English-only interactions excluded Hindi-speaking customers
Inconsistent experience - New customers got detailed guidance, returning customers had to repeat the same information every time
Zero cart recovery - When customers started but didn't complete orders, there was no systematic follow-up
Team capacity ceiling - Every new customer added manual burden; there was no path to profitable scale
Build a WhatsApp automation system that:
Eliminates manual order-taking while maintaining service quality
Creates separate optimized paths for new vs. returning customers
Operates 24/7 without requiring 24/7 staffing
Supports bilingual conversations with instant English ↔ Hindi switching
Recovers abandoned carts automatically without being pushy
Integrates seamlessly with Zeelab's existing backend systems
The goal wasn't just automation, it was creating an ordering experience that felt better than talking to a person, because it never forgot your preferences and was always available.
Phase 1: Understanding The Process and Users
New customers needed step-by-step guidance
Returning customers wanted shortcuts remembering previous orders
Both needed transparency about next steps
Language preference affected trust and completion
Phase 2: Mapping Complete Order Journeys
We created parallel order flows optimized for each customer type:
New Customer Path
Welcome & Language
Upload Prescription
Add Items
Enter Address
Verify Address
Cart Preparation
Review Cart
Select Payment
Track Order
9 Steps
Returning Customer Path
Welcome Back
Last Order
Repeat Order?
Same Address?
Skip to Cart
Prepare Cart
Review & Price
Choose Payment
Track Order
9 Steps
Returning customers skip 4 steps by confirming rather than re-entering data.
Phase 3: Creating Conversational Messaging
Every message needed to feel personal, not robotic. We wrote English and Hindi versions for every interaction.
Availability Gap
No after-hours service meant
lost night orders
English-only excluded
Hindi speakers
Returning customers repeated
same info
No systematic follow-up for
incomplete orders
More customers = More manual
work = No profitable scale
Language Barrier
Zero Cart
Recovery
team Capacity
Ceiling
Inconsistent
Experience
Example contrast:
Generic chatbot: "Please provide medicine name"
Our approach: "Let's get your medicines sorted! 📋 You can share your prescription image, or just tell me the medicine names, whichever works for you."
We built a main menu accessible anytime by typing anything:
This solved a critical chatbot problem: customers feeling trapped in linear flows. The menu gave them control and clear next steps, always.
Phase 4: Building The Automation in WATI
We used WATI's drag-and-drop chatbot builder to bring the journeys to life. The system used six node types working together:
Critical Features That Made It Work
1. Post-Order Flexibility
After placing orders, customers needed three capabilities:
2. Cart Abandonment Recovery
If someone started an order but didn't complete it, they received one gentle reminder after 15 minutes:
Then the system stopped. No bombardment. The goal was closing the loop on incomplete conversations without being annoying.
3. Instant Language Switching
Customers could start in English, switch to Hindi mid-order, then back again. The system followed their preference without breaking flow or losing context.
A rule-based WhatsApp chatbot that handles complete medicine ordering journeys—from initial inquiry to delivery tracking—with zero manual intervention for routine orders.
Unlike AI agents that improvise, we built predefined workflows designed specifically for Zeelab's operations. Think of it as codifying the pharmacy team's knowledge into automated conversation paths that maintain service quality while eliminating manual repetition.
What made it different:
Two optimized customer journeys (new vs. returning) instead of one generic flow
Bilingual support with instant switching, not just translation
Smart cart recovery that nudges once without nagging
Post-order actions (modify, track, cancel) built into the same conversation thread
Seamless backend integration for real-time cart pricing and order status updates
"
Flip HQ helped us bring structure and language to something we’d been trying to explain for months. Their work didn’t just improve our website, it changed how we talk about our product internally.
Abhishek kumar, Jugal Anchalia | Founders
Cobalt (now Rrefold AI)
