Three CSVs in. A cleaner card out. Every month.
ClearCard onboards in a single afternoon: three exports a facility already has, no EHR integration, no IT project.
The three files you already have
preference_cards.csv
What each surgeon asks for on every procedure card.
case_usage.csv
What was actually opened and used across past cases.
item_catalog.csv
What each item costs, so every recommendation carries dollars.
Three layers, one swappable pipeline
No single black box. Each layer answers a different question, behind a swappable Scorer interface.
Bayesian probability
The odds a given item goes unused, learned from the surgeon’s own history.
Quantile quantity
The right-sized quantity to keep on the card versus hold in the room.
Trend
Whether usage is drifting over time, so recommendations stay current.
Deterministic recommendations a surgeon signs off
Flagged items become plain-language recommendations rendered locally from templates (no LLM, zero hallucination by construction), each citing the surgeon’s own usage, a peer comparison, and a dollar impact.
Explain
Local, deterministic templates. Same inputs, same words, every time.
Approve
Surgeon approves, tweaks, or rejects each line. Nothing is automatic.
Export
The cleaned card exports back; next month’s usage re-enters the loop.
Walk the whole loop yourself.
The demo runs the full pipeline on a synthetic facility.
Open the demo →