Worked Example
A dental practice's new-patient intake, worked through end to end.
This is a realistic composite, not a real client, walked through in the same detail we'd use to scope actual work. It's here so you can evaluate how we think, not just what we claim.
The situation
A general dentistry practice with two locations gets around 40 new-patient inquiries a week: through the website contact form, their Google Business Profile, and after-hours voicemail. The front desk is handling patients in the chair most of the day, so inquiries typically wait two to six hours for a reply.
Response speed matters here more than most practices realize: scheduling data consistently shows conversion drops sharply once an inquiry sits past the first few minutes, well before a human ever gets to it.
What's actually automatable here, and what isn't
Not every part of this workflow should run without a person. Anything that reads as a dental emergency needs to reach a human immediately, not enter an automated queue. Insurance and clinical questions need firm boundaries on what the system is allowed to say.
The parts that are safe to automate are repetitive and low-ambiguity: reading a new inquiry, checking whether it is a new or returning patient, and proposing real open appointment times.
The five stages
Click a stage to see the technical detail behind it.
An inquiry arrives one of three ways: a website form submission (webhook), a Google Business Profile message (API), or an after-hours voicemail (transcribed via speech-to-text). Each becomes a single normalized event: raw text, source, and timestamp, dropped into a processing queue.
Where this breaks, and what happens then
The result
The structural change isn't that a computer replaces the front desk. It's that response time stops depending on how busy the front desk is at that exact moment, while a person still makes every judgment call that isn't mechanical.
Have a workflow like this?
Every engagement is scoped around the problem, systems involved, and desired outcome.