Vertically Integrated Behavioral Engagement

One model for
all your biology.

Your bloodwork, your genetics, your wearables, and your plate live in separate apps that never talk. The VIBE brings them into a single, living model of you — and turns it into guidance you can act on today.

118 biomarkers regulatory-RNA liquid biopsy wearable sync
The problem

Your health data is everywhere.
Your insight is nowhere.

A ring tracks your sleep. A lab prints a PDF. A diet app counts calories. None of them see the whole picture — and neither do you.

The VIBE was built on a simple premise: the signal isn't in any one test. It's in the correlations between them. When bloodwork, genetics, wearables, and nutrition feed one model, patterns emerge that no single stream can show — and that model gets sharper with every data point you add.

Four streams, one picture
01 / Blood

Clinical biomarkers

Metabolic, lipid, hormone, thyroid, and inflammatory panels — the routine bloodwork your doctor runs, made continuous.

02 / RNA

Liquid biopsy

Our proprietary regulatory-RNA analysis reads exosome-bound miRNA and snoRNA — a non-invasive window into disease microenvironments.

03 / Wearables

Everyday signals

Connect Oura, Apple Watch, Garmin, or Whoop. Heart rate, HRV, sleep, and training become continuous ground truth.

04 / Food

Nutrition intelligence

Photograph a meal. The VIBE estimates calories and macros, scores it against your biology, and suggests what to change.

The living model

A model of you
that keeps learning.

Supervised and unsupervised machine learning turn your combined data into predictive analytics — not a snapshot, but a trajectory that updates as you do.

Explore the platform

Collect

Order a panel, sync a wearable, snap your meals, or upload outside labs and scans. Every input is a data point.

Unify

The model fuses streams into one representation of your physiology, aligning genetic signals with everyday phenotype.

Predict

Biological age, metabolic health, and disease-risk signals surface patterns clinical research hasn't yet translated to practice.

Guide

An LLM health companion explains what changed, why it matters, and the next specific thing worth doing.

In the app

Answers, not just numbers.

Longevity

Biological age

See how old your body is behaving versus the calendar — and watch the gap move as your habits change.

Metabolism

Metabolic health score

One composite read on insulin, lipids, and inflammation, tracked over time so trends are impossible to miss.

AI

Health companion

Ask anything. The companion draws on peer-reviewed literature and your own markers to answer in plain language.

Nutrition

Photo food analysis

Snap a plate for instant calories and macros, scored against your goals and feeding your model in the background.

Data

Bring your own records

Upload physician labs, third-party genetics, or full-body MRI data to fold into the same analysis.

Clarity

Biomarkers, visualized

Every marker plotted, ranged, and explained — with the context to know whether a number actually matters.

The science

Regulatory RNA is the body's group chat.

Cells under stress — from a traumatic brain injury to a tumor microenvironment — release regulatory RNA into the bloodstream through intercellular signaling, much of it carried inside exosomes. Read those signals and you can distinguish disease states from a single blood draw. In one military cohort, our approach separated mild TBI from PTSD; published miRNA panels report AUCs above 0.90 for detecting TBI against healthy controls.

Basis: circulating miR-21, miR-92a, miR-425 and exosome-bound regulatory RNA — see the science page for references.

Read the full science
Evidence in the literature

Biological signals become more useful when models connect them.

Across independent studies, circulating and extracellular-vesicle RNA signatures have helped classifiers distinguish disease states—and combining molecular data with clinical context has improved performance further.

British Journal of Cancer · 2024 0.844 AUC

A five-miRNA small-extracellular-vesicle classifier identified follicular thyroid carcinoma in a 150-person multicenter validation cohort.

Read study
EBioMedicine · 2019 0.97 AUC

In an independent test cohort, a machine-learning model combining exosomal miRNAs with clinical records outperformed records alone for tuberculosis classification.

Read study
Multi-center study · 2025 1,385 participants

A 12-exosomal-RNA random-forest signature reported 0.915 AUC for separating eight cancer types from controls and also modeled tumor origin.

Read study

These results come from separate research cohorts and assays; they demonstrate the field's potential, not the validated performance of The VIBE or a substitute for clinical diagnosis.

Testing

Start simple.
Go as deep as you want.

Three panels, one model. Begin with core bloodwork or go all the way to genetic liquid biopsy — every result makes your VIBE sharper.

Compare panels
Base

~50 biomarkers

Metabolic, lipid, CBC, thyroid, and vitamin D essentials — the foundation of your model.

Advanced

~90 biomarkers

Adds hormones, advanced lipoproteins, inflammatory and autoimmune markers for a fuller read.

Ultimate + Genetic

118 + RNA signature

Everything, plus our proprietary regulatory-RNA liquid biopsy and epigenetic analysis.

0Biomarkers tracked
0.90AUCReported miRNA panel accuracy
0Data streams, one model
24/7AI guidance
Early access

Be first to see
your VIBE.

We're onboarding early members now. Join the list to get priority access, founder pricing, and updates as we open testing in your area.