Healthcare - Agentic Patient Relationship Management (PRM)
2025•Case Study
AI receptionist and workflow agents that cut scheduling time and reduce no-shows for clinics.
The Challenge
- 20 to 30 percent capacity lost due to busy lines and no-shows
- High admin overhead for scheduling and intake
- Siloed data and manual workflows across check-in, billing, follow-up
The Solution
Receptionist Agent for inbound calls and structured intake
Slot-Finder Agent integrated with CRM and availability validation
Summary Agent that generates structured pre-consult briefs
Reminder and Follow-up Agents via WhatsApp and SMS
Impact
Scheduling time reduced by about 70 percent
No-shows reduced by about 25 percent
Doctors receive consistent pre-consult summaries
Technical
Implementation Details
FastAPI microservices, n8n + LangGraph orchestration, Redis streams, schema-constrained GPT-4o summaries, observability with logs, metrics, and tracing.