An AI receptionist active on days off and after hours
A medical center with more than 40 doctors handles bookings, reschedules, cancellations and callback requests even when the front desk is unavailable.
Each card is a measurable path: context, problem, IGEA solution and what changes in the calendar and at the front desk. We add new cases as clinics share results.
It is a structured account of a medical center that switched on IGEA: who they are (vertical and setup), which bottleneck they had on the phone or recalls, which modules they used and what changed for missed calls, the calendar and front-desk load.
We publish the clinic name only with written consent. Until then cases stay anonymous by vertical (dental, multi-specialty, occupational medicine) with figures and processes we can verify internally.
The metrics used most often are answered calls on the main line, after-hours bookings, no-shows after reminders, hold time and front-desk hours freed from repetitive FAQs. Each case lists the effects observed on that flow.
Book a demo: we look at call volume, no-shows and WhatsApp flows, and whether it makes sense to measure IGEA on your main line.
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