We train models on your clinic’s own history, so you know what is likely to happen next week instead of finding out afterwards.
Reports tell you what happened. They do not tell you which of next week’s appointments will be missed, or which patients have quietly stopped coming back.
The data to answer both is already sitting in your bookings and your records. It has just never been used for anything except looking backwards.
Models are trained on your clinic’s bookings, records and outcomes, not on a generic dataset from somewhere else.
No-shows, patients about to lapse, demand by week and by treatment. Each prediction lands where the decision is made, not in a report nobody opens.
Every prediction carries how sure the model is and what it was based on. A number you cannot interrogate is not a number to act on.
Models go stale when the clinic changes. Yours are scored against what actually happened and retrained, rather than left to quietly drift.
From finding out afterwards to knowing in time to do something about it.
Roughly a year of bookings is where the patterns become reliable. With less than that we say so, and start with the predictions that need the least history rather than pretending the rest are ready.
No. These models predict operational things: attendance, demand, retention, and where enquiries come from. Anything touching diagnosis or treatment is a regulated medical device under EU rules, and that is not what this is.
It stays in your systems. Models are trained against your own database under your own access rules, and every prediction is written to the audit log like any other action.