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AI receptionist case study: how an eye clinic cut no-shows by 35%

Downloads | AI agents, AI case studies, Customer and CX leaders

A UK specialist eye clinic automated the first layer of patient contact: bookings, rescheduling, reminders and routine questions, across voice, SMS, email and web chat, in English and Urdu. Reception workload fell by over 70% and no-shows by 35%.

Anything messy still goes to a person. Complaints, edge cases and anything needing judgement stay with staff.

The clinic in numbers

  • 70%+ less reception workload
  • 35% fewer no-shows
  • 3 to 1 reception staff needed, with one overseeing the system
  • 2 secs the delay at which a call started to feel broken

Figures as reported by the clinic’s technical lead

How does the clinic’s AI receptionist work?

It sorts every contact into three routes: reschedule, ask about services, or book. It checks the calendar in real time, offers slots and confirms. Returning patients are recognised, and new patients register before booking. Anything outside the three routes goes to a person.

How did the clinic reduce no-shows?

With consistent reminders and easy rescheduling. Patients get a message two days before and again the day before, by SMS and email, and can move an appointment without getting through on the phone. High-priority follow-ups can trigger an outbound call.

What should you watch with a multilingual AI receptionist?

Language quality and speed. Native speakers had to test terminology, tone and formality, because direct translation fell over. Response delays above about two seconds made calls feel broken, so the team upgraded models and tuned the workflow.

Key takeaways

  • Automate the predictable layer. Bookings, reschedules, reminders and routine questions.
  • Keep the decision tree narrow. Three routes held up; crowded trees broke the voice experience.
  • Test languages with native speakers. Direct translation misses tone and formality.
  • Keep it under two seconds. Latency is what makes a voice agent feel broken.
  • Log every interaction. Central records made audits far easier.

What’s in the full case study

If routine calls are swamping your front desk, the full case study shows how this clinic built and rolled out its system:

  • The three-route call design
  • The stack and how each tool connects
  • The reminder schedule behind the drop in no-shows
  • How the clinic added a second language
  • The checks it ran on answers after launch

This case study first appeared in aiblBRIEF. Read the original article: Automating the first layer of customer contact.

Take the routine calls off reception

AI receptionist case study: how an eye clinic cut no-shows by 35%
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