Bidirectional, real-time FHIR
EMR-agnostic and live on the athenahealth Marketplace. cliexa reads the longitudinal record and writes the signed note back to the EMR.
EMR-agnostic and live on the athenahealth Marketplace. cliexa reads the longitudinal record and writes the signed note back to the EMR.
Deploy where you need it, with reference architectures available for major cloud and government environments. Ready to deploy in 3 months.
HIPAA-covered processing, with Business Associate Agreements spanning the full AI stack and documentation available under NDA.
Every capability runs behind your own product, under your own interface: documentation scoring, medical-necessity validation, denial risk, and appeals as modular APIs.
Turn on one Impact Area or the whole platform on the same integration: documentation, denial risk, or the full stack. Every system you already run stays in place.
Outcomes, approvals, denials, and appeals feed back into the reasoning core, what works is reinforced, what fails is corrected.
One reasoning layer between the tools that collect data and the systems that run on it.
Traditional systems run inside-out, schedule, visit, document, order, treat, bill, then validate quality, compliance, and payment after the fact. cliexa reasons outside-in, surfacing the compliant, patient-specific pathway before and during care.
Schedule → Visit → Document → Order → Treat → Bill
Payer reality → Provider protocols → Patient state → Care
Every answer opens up: when cliexa flags a patient or a claim, it shows what it concluded, exactly which findings drove it, the guideline it was measured against, and the next step it suggests. A deterministic rules layer sits beneath the reasoning engine, so the same inputs always produce the same call.
Every output traces back to payer rules, clinical protocols, and the patient’s own record. When the record is thin, “insufficient evidence” is a real answer.
In a peer-reviewed study, cliexa agreed with clinicians 90.5% of the time. In Mayo Clinic Platform’s evaluation, the OUD model reached 97% accuracy.
A clinician signs every final answer. Encoded rubrics keep scoring auditable and screened for bias and fairness before production.
Walk the architecture with us, the reasoning core, the module ring, and the source trace behind every answer, mapped to your integration, documentation, and payer requirements.