Determinism first
The rule engine identifies structured findings before any draft is written. AI never invents clinical facts.
A bounded decision-support flow that unifies messy real-world data, runs it through versioned rules, surfaces only what matters today, and routes every action through the licensed clinician.
Each phase is independently auditable. Each phase can be paused, amended, or rolled back without affecting the others.
Pull genomic reports, lab panels, medication lists, problem lists, allergy lists, and wearable summaries into one FHIR-shaped patient context. Every field carries its source.
Versioned rules check phenotype calls against active medications, lab thresholds against medication context, and wearable trends against initiation events. The rule engine fires before any language model touches the chart.
From a typical chart of 8+ findings, the platform pulls forward the 1-3 items tied to today's appointment. Longitudinal context collapses behind a single expander so the today view stays clean.
Co-sign on prescribing-relevant accepts. Suppression with rationale. Amendment lineage. Hash-chained audit. Every action is reversible, attributable, and exportable.
The product is built around a posture that puts evidence and reversibility ahead of speed.
The rule engine identifies structured findings before any draft is written. AI never invents clinical facts.
Every recommendation references a guideline source (CPIC / PharmGKB / USPSTF / ADA / AHA) and a versioned rule ID.
Accept, dismiss, snooze, amend — all logged. Nothing the platform does is uneditable.
Medication changes are made only by the licensed clinician. The product is decision support, not a prescriber.
Open Jane Smith's patient page. The four phases of the loop are visible as you scroll: storyboard header (unify), interaction alerts (interpret), today panel (surface), review actions (verify).