Client Overview
Activbase is India’s most advanced Sports and Orthopaedic Rehabilitation Centre, located in Kochi, Kerala. The centre specialises in injury rehabilitation, post-surgery recovery, and structured return-to-sport programs for both athletes and non-athletes.
With increasing inbound enquiries from ads, WhatsApp, and organic channels, Activbase required a structured, automated conversation system to:
- Educate users clearly about treatment scope
- Filter serious and location-eligible leads
- Reduce unnecessary manual follow-ups
- Set correct expectations (no instant or single-session cure claims)
Business Challenge
- High volume of unstructured enquiries related to different injuries
- Users from multiple cities across Kerala, many outside Kochi
- Repetitive manual questioning by staff (injury, location, eligibility)
- Risk of miscommunication, especially around treatment duration
- Need to hand over only qualified, visit-ready leads to the tele-calling team
Solution Implemented
An AI Agent–driven WhatsApp Conversation Flow was designed and deployed to act as the first point of interaction, handling education, qualification, and lead staging automatically.
The flow was built with clear logic gates, location validation, and ethical medical communication rules.
AI Conversation Flow Structure
1. Initial Welcome & Education
The AI agent introduces Activbase, clearly positioning it as:
- A sports & orthopaedic rehabilitation centre
- Focused on recovery, rehabilitation, and return-to-activity
User Education Flow
User Education Flow: The bot educates users by listing treatable conditions
The bot educates users by listing treatable conditions such as:
- ACL / PCL / Meniscus injuries
- Sports injuries
- Muscle & joint pain
- Back pain, sciatica, disc issues
- Post-surgery rehabilitation
Purpose: Set context, authority, and relevance before collecting any data.
2. Injury Identification → Lead Capture
Once the user mentions their issue, the AI:
- Acknowledges the concern
- Requests Name + Phone Number in a single message
Purpose
- Reduce drop-offs
- Capture clean CRM-ready data
- Maintain conversational flow
3. Location Identification
After lead details are captured, the AI asks:
“Which city or location are you currently in?”
Purpose
Location-Based Qualification Logic (India Only)
A. User from Kochi / Ernakulam
- AI confirms proximity to the centre
- Lead is marked AI Interested
- User is informed that a tele-calling representative will connect within 2 working days
👉 Outcome:
High-intent, immediately actionable leads sent to the team.
B. User from Kerala (Outside Kochi)
The AI checks willingness to travel:
If YES:
- Lead moved to AI Interested
- Team follow-up confirmed within 2 working days
If NO:
- Lead moved to Not Eligible / Not Interested
- AI politely communicates in-person treatment limitation
- Keeps the door open for future contact
👉 Outcome:
Sales team avoids time spent on non-convertible leads.
Global Safety & Trust Rules Embedded
To maintain medical credibility and compliance:
- ❌ No single-session cure promises
- ❌ No unrealistic recovery timelines
- ✅ Clear explanation that recovery depends on condition severity
- ✅ Consistent response for common questions like call timelines
This ensured ethical communication while still driving conversions.
Results & Impact
Location Identification – To apply location-based eligibility logic before passing the lead to sales
- ✅ 100% automated lead qualification before human involvement
- ✅ Reduced manual workload for the front desk & calling team
- ✅ Higher lead-to-consultation conversion quality
- ✅ Clear expectation setting → fewer drop-offs post-call
- ✅ Scalable system ready for ad-driven traffic growth
Why This Stands Out (Aura Awards POV)
- Practical AI implementation with real business impact
- Strong balance of automation + human handoff
- Ethical AI usage in a healthcare-adjacent domain
- Clear logic, clean CRM stages, zero fluff
Final Takeaway
This AI Agent didn’t just answer questions — it acted as a smart front-desk executive, ensuring that only relevant, eligible, and informed leads reached the Activbase team.
A textbook example of AI-first operational efficiency in healthcare marketing.