Modeled scenario · Healthcare · 8 employees
An 8-person outpatient clinic
target · no-shows 18% → 11%
An AI front desk keeps the booking, reminder and reschedule loop running while one person covers the desk.
The starting point
The clinic has one front-desk staff member handling phones, check-ins and scheduling. Patients call during lunch breaks or after hours and leave voicemails that pile up. In this scenario no-shows run at 18%, which means lost revenue and idle providers.
The deployment
The clinic scopes an AI front desk around text-message scheduling and reminders. Patients text to book, reschedule or ask about preparation instructions, the AI drafts against the live calendar, and reminders go out on a fixed schedule the clinic sets.
- Booking and reschedule replies drafted against the clinic calendar, around the clock.
- Reminders scheduled 48 hours, 24 hours and 2 hours before the visit.
- Pre-visit instructions attached by appointment type.
- Anything clinical, and every cancellation, goes straight to a person.
The targets we model
Patients answer texts faster than phone calls, the desk spends less time on repetitive scheduling, and the no-show rate moves toward 11%. The tiles below are the targets a pilot of this shape runs against.
18% → 11%
No-show rate
100%
Appointment reminders on a schedule
22
Front-desk hours handed off per week
24/7
Booking window
Targets for a pilot of this shape · not measured results
A 9 p.m. reschedule by text beats a morning of voicemail callbacks — for the patient and for the front desk.
Why this scope works
The rollout starts with a single high-friction workflow: appointment reminders. Once that runs reliably, booking and rescheduling follow. Medical questions and sensitive cases keep a short path to a person, which is what keeps staff and patients comfortable.
Method · AI front-desk
How this scenario is built
Nothing above came from a customer account. It came from four inputs and one multiplication, both shown here, so you can check the arithmetic and then argue with the assumptions.
01 · Input
The routine loop we start from
The “Healthcare front desk” row of the ROI calculator puts 40 hours a week into the repeatable part of this job. The scenario runs one employee against that loop.
02 · Input
The share we assume moves to the machine
The share of that loop the AI takes on. It is the one number we choose per scenario, and it is the slider you move on the calculator — everything else follows from it.
03 · Arithmetic
Hours freed, and what they cost today
At $35 an hour loaded — salary, taxes, tooling and management time — 22 hours a week is $3,334 a month of routine time, against $149 a month for one employee. Same formula as the calculator, same weeks-per-month constant of 4.33.
04 · Targets
The percentages are targets, not measurements
Uplift in meetings, resolution share, no-show rate: each one is a target agreed before a pilot starts and then measured in your own systems. No figure on this page comes from a customer account.
05 · Assumed
What this scenario assumes we would connect
The scenario assumes a text-message channel and a booking-calendar connection. Unistaff ships no SMS provider and no calendar connector today, so a deployment of this shape starts by scoping both — and a clinic carries health-data obligations we do not claim to cover.
Same inputs, same formula — swap in your role, your hours and your loaded rate.