mooveo.
Master every moove.
Most wearables tell you how yesterday went. mooveo tells you what is happening right now. Built for people who train on data, it is the body performance console that unifies every wearable into one real-time view — raw signals processed on the device for instant feedback, cloud AI for depth and history.
The wearable market is fragmented by design.
The wearable market is fragmented by design. Users end up dashboard-hopping: one app for recovery, another for sleep, a third for load. No single view. No live signal during effort. No explanation of what moved the number.
Whoop locks you to its subscription. Garmin stays inside its own ecosystem. Apple Watch ignores every other band you own. If you train with multiple devices or cancel a hardware subscription, your data dies with it.
Users end up with one app for recovery, another for sleep, a third for load. No single view. No live signal during effort. No explanation of what moved the number.
No app unifies all major brands with real-time feedback during effort. The clearest white space in the market — mooveo fills it.
One console. Every signal. Live.
mooveo connects Apple Health, Health Connect, manufacturer APIs, partner accounts and OpenStrap for WHOOP bands. Whatever tracker you own, the data flows into one place. The EU Data Act is moving the regulatory ground in this direction.
The clearest white space in the market. Most competitors summarise yesterday. mooveo processes latency-sensitive signals on the device so feedback arrives while the effort is still happening — not after the cool-down.
Latency-sensitive computation runs locally. Marginal cost per free user is close to zero. Heavier models, long-term trends and the AI coach would run in the cloud. That compute is what a future paid tier would be built on — pricing is not defined yet.
Every metric shows what moved it. Contributors visible, thresholds personal, calculations transparent. Oura does this well. Coros does it differently. mooveo aims to do both — with planned action levels so a number is never just a number.
Raw data stays local by default. No cloud lock-in on the free tier. Cycle Sync and health-sensitive data sit behind separate explicit consent. GDPR-compliant from day one, not retrofitted.
120 USPs from 14 competitors mapped to concept areas — readiness, exertion, recovery, movement, energy, AI coaching. Early planning: module count and names are not defined yet. The USP Atlas sets the direction and guardrails (no hardware-only sensing, wellness wording only, Heart Lab deferred) — not the final module list.
Edge-first architecture, cloud depth on demand.
Latency-sensitive computation runs on the device — no round-trip, no server cost per free user. The AI coach and long-term trend models would live in the cloud, likely behind a future paid tier. This split is not just an engineering decision: it is the business model. The free tier is genuinely free because its marginal cost is near zero. A paid tier — pricing not yet defined — would cover the compute that earns it.
Built around the athlete, not the hardware.
Early concept exploring HRV, resting HR, sleep quality, and load history. Not yet defined as a module.
Early concept for real-time effort feedback. Would process heart rate and motion on-device so feedback arrives during the set, not after.
Early concept exploring sleep stages, respiratory rate, and HRV trend. Not yet defined as a module.
Early concept around activity type, intensity distribution, and sedentary gaps. Not yet defined as a module.
Early concept integrating load, recovery, nutrition signals, and chronotype. Not yet defined as a module.
Early concept for an AI coach — natural-language Q&A about training decisions, pattern detection. Not yet defined as a module.