PNOĒ is not just a metabolic testing device.
It is a complete growth infrastructure for wellness, longevity, and performance facilities that want to increase acquisition, retention, and revenue — without increasing complexity. From clinical-grade hardware to all-inclusive intelligent software, white-labeled client deliverables, AI agents, and business support, PNOĒ installs a repeatable system for growth inside your facility.Here
Measure better. Convert faster. Retain longer. Scale smarter.
Every growth engine starts with differentiation. PNOĒ delivers instant, non-invasive metabolic diagnostics in just 8 minutes
— no blood draws, no lab delays, no operational friction. The portable device integrates seamlessly into your intake flow and elevates perceived value from day one.
Each assessment captures 23 respiratory and metabolic biomarkers, including:
Objective data positions you as premium. Diagnostics
become your lead generator.







Turn Collective Data Into Clear
Decisions, Automatically
Once captured, diagnostics are centralized inside PNOĒ’s Health Dashboard, where breath analysis, labwork, and wearables are evaluated collectively. The system translates biomarker thresholds directly into service recommendations you offer, using structured logic and AI support.
Using the Logic Builder and AI layer, you:
Identify metabolic, cardiovascular, or respiratory limiters
Recommend specific services you already offer, based on biomarker thresholds
Define prescription structure (frequency, duration, retest cadence)
Scale decision-making without increasing headcount
Preserve clinical control while automating execution
This is where conversion increases. Every assessment becomes a prescription tied to revenue.
Objective diagnostics increase assessment-to-program enrollment.
Adaptive programming and retest cycles extend client lifecycles.
Data-driven upsells connect clients to services you already offer.
Fitness Studios & Gyms
CrossFit & HIIT Facilities
Med Spas & Longevity Clinics
PNOĒ installs a scalable growth engine inside your model.