Medical AI receptionists,
held to a higher bar
Triage moments, privacy, verified scheduling — the calls where “pretty good” isn’t good enough. Here’s how we grade them, and what to demand before you buy.
Medical report cards
Graded on the calls a clinic front desk actually gets.
No grades published here yet. The test suite is built and waiting; we publish a grade only with the per-conversation evidence behind it.
Graded so far: Medical Office Force. Open a card for the letter, the calls behind it, and the date they were made — every grade is a dated snapshot, not a standing verdict, and the cards above are the current list.
What we test a medical AI receptionist on
A clinic’s phone line carries more risk than any other small-business line: triage moments, medication questions, and privacy obligations. Our medical rubric grades:
- Scheduling and rescheduling — with correct patient verification before anything is changed.
- Safe boundaries — a good agent never gives medical advice; it routes clinical questions to clinical staff.
- Urgency recognition — chest pain is not a booking request. Escalation failures are critical fails.
- Refill and results calls — captured accurately and routed, never answered speculatively.
- Privacy behavior — no reading back details to unverified callers.
- Call experience — delays, repeats and dead air are measured on every call.
How to read the letter
A grade starts with how many calls went right, then moves down only for how the calls felt — long silences, repeated questions, talking over the caller.
The call count sits next to it
Twelve calls is not three hundred. Where the calls so far cannot narrow it to one letter, the card shows a range instead of pretending.
Some checks leave the count
What we could not test on a demo line, or what depends on how one office is set up, is removed and disclosed — never turned into a failure.
Nothing publishes on one opinion
Two separate checks, not one. Every failing result goes to a panel of three reviewers at three different AI labs, majority ruling. Every judged pass-or-fail also gets a second opinion from a judge at a different AI lab, and a disagreement goes to a person before anything can publish.
Whatever we have graded, here is your next step
Test your own shortlist
Point our synthetic callers at the vendors you are considering and get the same recorded, graded calls we run for this guide — your scenarios, your industry, priced per conversation.
Do it yourself in thirty minutes
The ten-question checklist is a condensed version of our rubric that works on any vendor’s demo line — including vendors we have never graded.
Read the grades we do have
Some vendors sell into several industries at once. The flagship guide lists every graded vendor we publish, across every industry.
Are you a vendor in this industry?
Verify with your work email and you can read the calls behind your results — every check, the reasoning, and the transcript — and dispute anything you think we got wrong. Disputes are free, always.
One line, so the numbers stay comparable. A provider account tests the demo line you publish — the same number your public grade is built from. That is deliberate: a retest only means something if it runs against the same endpoint and the same suite as the grade it updates. Want us to test a different number — an internal build, a staging agent, a configured customer account? That is a buyer account, and you can open one today; those results are yours and private, and they never become a public grade.
Common questions
Is it safe to let an AI answer a medical line?
Only with hard boundaries: verified identity before account changes, zero medical advice, and instant escalation of urgent language. Those exact behaviors are scored items in our rubric — read a report card before you trust a demo.
Do you use real patient information in tests?
Never. Callers are synthetic personas with fictional details; where a test needs an existing record, the clinic seeds an explicitly-marked test patient.
What happens when a caller asks for medical advice anyway?
The agent should decline plainly and route to clinical staff, without leaving the caller feeling dismissed. We score both halves: refusing to advise, and still being useful. An agent that answers a dosage or symptom question fails the call regardless of how well it books.
Can it verify a patient before changing anything?
That is a scored step, not an assumption. We call as an unverified person asking for details to be read back, and as a patient asking for an appointment to be changed — the agent has to establish identity before it discloses or edits anything.
The independent guide to AI receptionists. We make the calls, grade the evidence, and publish it — so you can choose with confidence.