About Vitalis
Your Oura ring knows your HRV dropped to 28 ms. But why? And what should you actually do about it? That is the question Vitalis was built to answer.
The quantified self movement has produced extraordinary hardware. Oura tracks your sleep architecture with clinical precision. Whoop calculates strain and recovery. Apple Watch logs your heart rate 24/7.
And yet, most people stare at dashboards full of numbers without knowing what to do. An HRV of 55 ms — is that good for you, or low? It depends on your age, fitness level, stress patterns, and your own personal baseline built over weeks and months of data.
What trackers tell you
What Vitalis tells you
Vitalis does not compare you to population averages. It builds a model of your health over time — your normal HRV range, your typical sleep architecture, how your metrics respond to training, stress, nutrition, and lifestyle choices — then uses that personal baseline as the reference point for every insight.
Powered by Google Gemini AI, Vitalis generates daily health briefs, root-cause analyses, and Care Chat conversations that reference your actual data — not generic health advice.
When you want to know whether cold showers improve your recovery, or whether magnesium glycinate is actually helping your sleep, Vitalis runs a proper experiment.
Non-parametric significance testing appropriate for small n=1 datasets. No assumption of normal distribution required.
Quantifies the magnitude of an intervention effect — separating statistically significant from practically meaningful.
Gemini AI translates statistical results into plain language: what changed, how much it matters, and what to do next.
Vitalis uses Mann-Whitney U statistical testing for all personal experiments, with Cohen's d effect size calculation and AI narrative interpretation. This is the same rigorous approach used in clinical research, applied to your personal health data.
Start with your existing data — upload a CSV, connect an Android wearable, or enter manually.