Your next 90 days, before they happen
Revenue forecasts. No-show predictions. Churn alerts. Segment LTV scores. All built from your practice data — and updated every hour with confidence intervals, not just point estimates.
Every drop in bookings, every lost patient — the pattern was in your data weeks earlier
Six forecasts, running right now against your data
Not academic. These are the predictions that actually move dollars — and the ones your gut currently makes without help.
Revenue forecasting
Next 30 · 60 · 90 days
Point forecast with a confidence band. Never just a number — always a range you can plan against.
No-show prediction
48h before the appointment
Every scheduled visit scored on no-show risk. High-risk ones get an extra reminder — or a courtesy call.
Patient churn alerts
Before they slip away
Flag patients whose booking cadence has shifted. Reactivation outreach fires while there's still a relationship.
Insurance denial prediction
Before the claim ships
Score claims on denial risk before submission. Flagged ones get a coding review; the rest go through untouched.
Capacity forecasting
For smarter staffing
Predict busy vs slow days two weeks out. Shift capacity, adjust hours, add hygienists — before demand hits.
Segment LTV scoring
Where the value actually is
Score patient segments on projected lifetime value. Marketing dollars, retention effort, referral rewards — targeted at the right cohorts.
Every prediction, the same five stages
Ingest → train → predict → alert → explain. Once an hour, per model, per account.
Signals in
Pull from your PMS, marketing, financial, and communication data — every hour.
Models fit
Models trained on your practice's unique patterns, not industry averages.
Forecasts out
Point estimates plus confidence intervals — never just a single number.
Anomalies flagged
When a metric drifts from its prediction, your team gets pinged — with reasoning.
Traced to source
Every prediction linked to the signals that drove it. No black boxes.
One engine, every signal
Your PMS, ads, payments, communications — all flowing into one forecast surface, all traceable back to source.
What the models will never do
Six commitments enforced in the training pipeline — not policy alone.
Never predicts individual health outcomes
Predictions cover business metrics — bookings, revenue, churn. Never diagnostic or clinical outcomes. That's medicine, not analytics.
Never uses protected class attributes
Race, religion, gender identity, disability status — excluded from every model as inputs and outputs. Enforced in the training pipeline.
Never presents predictions without confidence
No point estimates alone, ever. Every forecast comes with a range, and every alert comes with a confidence score. Uncertainty is a feature.
Never trains across practices without consent
Your data trains your models. If we want to use aggregated data for a benchmark model, we ask — opt-in only, aggregated only.
Never black-boxes a decision
Every prediction is traceable to the signals that drove it. If a patient is flagged high-risk, you see exactly why. No “the model said so.”
Never replaces clinical judgment
Predictions inform decisions — they don't make them. A no-show risk score is a nudge to send an extra reminder, not a reason to overbook the slot.
Every signal your practice already generates
We connect to the systems your practice already uses. No new logging, no manual entry — the signals are already there.
Custom data source? If it has a query interface or export, we can ingest it. More data = tighter confidence intervals.
The commitments, every prediction inherits
Predictions without accountability are guesses. Every forecast, every alert, versioned and reviewable.
Predictions are only useful when they're accountable
Every model version is logged. Every alert carries feature importance. Every forecast comes with a confidence interval. Nothing runs in a black box — not the models, not the anomaly detectors, nothing.
What we hold ourselves accountable to
Operational commitments — not marketing numbers.
The predictions, answered
The questions we get from practice owners, IT leads, and skeptical clinicians.
01
Where does our patient data live — do you take it?
Compliance
It stays in your PMS. We pull only the fields we need for prediction (bookings, cancels, spend, demographics — never diagnosis or treatment content) through your existing HIPAA-compliant connections. We aggregate and model — we don't stockpile.
02
What happens when the forecast is wrong?
Accuracy
Every prediction comes with a confidence interval, not a single number. If the actual falls outside the interval, we retrain and flag it as a model-quality issue. Forecasts are wrong all the time in the tails — that's what the interval is for.
03
Can we see how the model makes a prediction?
Ownership
Yes — every alert comes with feature importance. If we flag a patient at high no-show risk, you see exactly which signals drove it (previous no-shows, appointment lead time, day of week, distance, etc.). No black boxes.
04
How much historical data do we need?
Setup
Minimum 90 days for basic forecasts, 12 months for reliable ones. Less data = wider confidence intervals, not worse predictions — the model tells you what it doesn't know. If you have less, we start with simpler predictions and grow into the harder ones.
05
Which predictions are most reliable?
Accuracy
Aggregate ones (30-day revenue, weekly bookings) beat individual ones (this-patient no-show risk) — that's always true. We're transparent about which is which. If a prediction is under 70% confidence, we don't alert on it.
06
What if we're a brand-new practice with no data?
Setup
We use industry-benchmark models to bootstrap, then swap them out for your data-trained models as history accumulates — usually within 4–6 months. You'll see it happen in the model versioning log.
Want us to forecast your next quarter?
Share read access to your PMS. Within 48 hours, we'll come back with a 30-day booking forecast, top-3 no-show risks flagged in your schedule, and one anomaly worth investigating — free, no obligation.
See what your practice will do next.
Share view-only PMS access. Within 48 hours, we'll walk you through a live 30-day forecast for your practice, the top-3 no-show risks in your current schedule, and one anomaly worth investigating — free, no commitment.