We are building the predictive infrastructure for the $1.5 trillion obesity care category — and we own the behavioral prediction space no one else owns.
GLP-1 medications have rewritten obesity treatment. But two out of three patients drop out within a year, and most regain the weight after stopping. The drug works. The behavior fails. Ew2health is the AI prediction layer that fixes the leak — already deployed, already revenue-generating, and validated in 30+ pilots.
The problem
Obesity is the defining metabolic challenge of our generation — and the systems built to treat it are bleeding patients, revenue, and outcomes.
2B
people affected globally
$1.5T
annual financial burden worldwide
€10B
looming Netherlands healthcare bill
65%
patient dropout rate in obesity programs
Clinics invest heavily in patient acquisition, only to watch two out of three leave before achieving lasting outcomes. The financial impact is devastating. The clinical impact is worse.
Where we sit
Obesity care is a stack: manufacturers make the drug, programs prescribe it, and coach and monitor their clients. Ew2health owns the prediction layer that all programs can use: to detect who will stay and succeed, so programs can intervene and achieve better clinical and economical results.
The medication
The manufacturers — they make the GLP-1 drugs
The programs that deliver it
Prescribe, coach & monitor — telehealth · apps · clinics · RPM
The prediction layer
Predicts who will stay and succeed — the intelligence all programs run on.
Ingests: Garmin VO₂max · smart scales · CGMs · check-in behaviour
Programs come and go. The prediction layer they run on doesn't. That is the space Ew2health occupies.
The competitor landscape
Ew2health with Sinque is unique in that it monitors behavioral signals to predict behavior: who drops out and who doesn't. Monitoring many do; prediction is the open quadrant.
PREDICT — forecast outcomes
Biometric signal
Behavioral signal →
Biometric signal
Predict biology — for pharma R&D
Dandelion
(data → pharma R&D)
+ RWE / precision-medicine players
Predict behavior — who will succeed
forecasts who stays & succeeds
Clinician RPM — biometric monitoring
Rimidi · CoachCare · HealthSnap · Vitalera
fed by CGMs · smart scales · vitals
Consumer apps & coaching — behavioral
Noom · Embla · WeightWatchers · MyFitnessPal · Second Nature · Oviva · Yazen
track the person — but don't forecast
Behavioral signal
MONITOR — track & alert
The defensible moat
This is not a feature set. It's structural defensibility — patented, validated, embedded, and self-reinforcing. Any single layer is copyable; the combination is the moat.
Our numberless dial shows direction — Losing / Maintaining / Gaining — not a raw number, so patients keep checking in instead of dropping off. That daily check-in is a behavioral signal on who's engaging that no competitor collects — and it's the raw material every prediction runs on.
US Patent 11,633,160 protects our method of forecasting weight trajectory from behavioral signals. Others connect the same devices and monitor the body; we forecast who will succeed. It's a method patent, not a model patent — the defensibility is structural, not cosmetic.
The forecast becomes prioritized action: which patients to contact, and when. Once the Sinque view is what a care team runs on each morning, it's embedded in the clinic's workflow — and switching costs become structural, because replacing it means rebuilding the routine, not swapping a tool.
More patients generate more data. More data sharpens predictions. Sharper predictions drive better outcomes. Better outcomes attract more clinics — and a two-sided network of clinics and health professionals is emerging on top. The loop compounds, and a competitor can't start it retroactively.
Compounding loop
Each layer compounds the next. Competitors cannot start the loop retroactively.
Strategic validation
Ew2health has been chosen by world-class healthcare and technology partners — at the highest standards of clinical and commercial rigor.
DATA ANALYTICS
First Netherlands-based startup selected for the Mayo Clinic Platform_Accelerate program. Building advanced predictive models against tens of thousands of GLP-1 treatment records — improving our analytics at the highest standard of medical excellence.
Real-world deployment
Two pilots — Motiva (12 months) and MotivAÇÃO (6 months) — produced 7.34 kg average weight loss versus 1–1.5 kg in standard care, and 87% retention at 6 months versus a 20–50% benchmark.
Clinical research
Pilot deployment at one of Latin America's most respected medical institutions. The relationship continues as Ew2health expands its clinical research footprint.
Ecosystem partnerships
Strategic integrations with Roche (CGM data) and Garmin (VO₂max wearables) extend our 3D biomarker architecture — and create deep ecosystem barriers competitors cannot easily replicate.
Working alongside
Proven impact
These numbers come from real-world pilots and active deployments. They are not projections — they are what happens when behavioral prediction is embedded in clinical workflow.
>2×
better outcomes, as behavioral intelligence improves adherence and treatment success
Clinical outcomes
25%
greater efficiency driven by attention triage and remote patient monitoring
Operational efficiency
50%
higher cash generation, driven by retention and efficiency
Economic impact
Pilot data sources: Petrobras Workplace Nutrition Program (Motiva 12-month, MotivAÇÃO 6-month), Brazil. Active clinic deployments, Netherlands.
The expansion path
Three customer horizons, each one larger than the last — and each one validated by what we already deliver today.
Now · 2026–2027
Our buying customer today. Active in the Netherlands and Brazil, generating recurring revenue, real-world clinical data, and the operational proof that anchors everything that follows.
NL · BR
Next · 2027–2029
Licensing the platform to scale behavioral intelligence across virtual networks. Expansion into the United States and United Kingdom, followed by Latin America.
US · UK · LATAM
Strategic · 2029+
Ew2health becomes predictive infrastructure for GLP-1 retention and the clinical-grade intelligence layer for continuous diagnostics. India, China, Middle East. Strategic exit optionality surfaces.
GLOBAL
The team
A Brazilian physician applying machine learning since 2023. A Dutch applied physicist with corporate scale experience at BCG and Cargill. An American operator with international business expertise. The combination is deliberate — clinical credibility, strategic ambition, operational discipline, and multicultural backgrounds, are all required to build global infrastructure for a category.
Full team and bios on our about page.
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