Build AI health coaches with
data you control.
Wearable data ingestion, health scoring, and AI reasoning, everything you need to build personalized coaching experiences without building the data layer from scratch.
The data layer is eating
your roadmap.
Building an AI health coach means solving the data layer before you write a single prompt, and that is where most of the timeline goes. Open Wearables handles it: one unified REST API across all major wearable providers, normalized and deduplicated into a shared schema, with documented health scores computed on top. Sleep Score and Resilience Score turn raw sensor readings into values a model can reason about, and an MCP server exposes those scores, trends, anomalies, and baselines to Claude, ChatGPT, or any other LLM. That distinction matters for coaching quality: a model given interpreted health context produces better guidance than one handed a wall of raw numbers, and it can explain its reasoning because the scoring logic is open. Self-hosted and MIT licensed, so user health data never leaves your infrastructure and no vendor sits between your coach and its inputs.
You want to build an AI coach that understands a user's body. Instead, you're spending months wrangling OAuth flows, normalizing heart rate formats across six providers, and reverse-engineering what "recovery" even means.
By the time the data pipeline works, your differentiation, the coaching logic, the personalized recommendations, the UX that keeps users coming back, hasn't been touched.
Open Wearables handles the data layer so you can focus on the coaching layer. Connect wearables, compute health scores, and feed structured reasoning to your LLM, all from a single self-hosted platform.
Coaching experiences
powered by real data.
From endurance training to chronic condition management, the same platform powers every coaching use case.
Endurance Training
Combine strain scores, HRV trends, and recovery data to build AI coaches that periodize training, flag overtraining, and adjust volume in real time.
Weight Management
Use activity, sleep, and stress scores to contextualize nutrition plans. Help users understand why weight fluctuates and what to adjust.
Sleep Optimization
Surface sleep stage data, consistency scores, and environmental correlations. Build coaches that recommend actionable bedtime routines.
Stress Management
Track HRV, stress scores, and recovery patterns. Coach users through breathing exercises, workload adjustments, or rest days when their body signals distress.
Nutrition Coaching
Layer wearable data on top of meal logging. Correlate food timing with energy, sleep quality, and recovery to personalize dietary guidance.
Chronic Condition Support
Monitor resting heart rate, HRV baselines, and activity trends over months. Build early-warning systems for flare-ups, relapses, or deconditioning.
From raw signals
to coaching output.
Four layers that turn wearable data into structured reasoning your LLM can act on.
Connect
Users link their wearables via OAuth. Open Wearables normalizes data from all major wearable providers into a single unified schema, heart rate, sleep, activity, and more.
Score
The platform computes open health scores: sleep quality, recovery readiness, strain load, stress index. Every algorithm is auditable and tunable to your population.
Reason
The AI engine detects trends, flags anomalies, and connects patterns across scores. It outputs structured reasoning, not raw numbers, via an MCP server for any LLM.
Coach
Your LLM consumes the reasoning output and delivers personalized coaching through your app. You control the tone, the domain focus, and the recommendations.
The coaching platform
you actually own.
No vendor lock-in. No black-box algorithms. Full data ownership. Build coaching features on a foundation you control.
Open Algorithms
Every health score is open source. Audit the logic, tune thresholds for your population, or fork and build your own.
Infrastructure-Only Costs
No metered API calls and no usage tiers. Your costs are infrastructure only, the same servers you'd run anyway.
Self-Hosted
Deploy on your infrastructure. Health data never leaves your servers. HIPAA-ready architecture with full data lineage.
Any LLM
MCP server works with any model, OpenAI, Anthropic, Llama, Mistral, or your own fine-tuned model. No vendor lock-in.
Stop building
the data layer.
Start building coaching.
First API call in 5 minutes. Coaching features in days.