Name: Open Wearables
Author: Open Wearables

Question 1

How long does integration take?

Accepted Answer

Basic setup takes minutes using Docker. Open Wearables itself deploys in minutes but you need to apply for API credentials with each wearable provider (Garmin, Oura, etc.). Provider approval processes vary — some are immediate, others take weeks. It's a one-time process, and it's the same whether you use Open Wearables or build integrations yourself. Once you have credentials, the actual integration (OAuth flows, data sync, testing) takes days, not months.

Question 2

Do you need to apply for API credentials yourself?

Accepted Answer

Yes. You apply directly to each wearable provider (Apple, Garmin, Oura, etc.) for API credentials. This typically takes 1–4 weeks per provider. You create developer accounts with each platform, submit applications explaining your use case, and receive OAuth client IDs and secrets. These credentials live in your environment variables, not in a vendor's system. The benefit: you own the relationship with wearable providers directly. The tradeoff: you handle the application process yourself, though Momentum can guide you through it if needed.

Question 3

Are there any per-user fees in Open Wearables?

Accepted Answer

No. Zero per-user fees. You only pay for your own infrastructure costs (hosting, database storage), optional expert services or custom features from Momentum (if needed), and LLM API costs if you use AI chat features. Compare this to SaaS solutions charging $1–3+ per active user — for B2C apps with thousands of users, those fees can consume 20–40% of your margin just for wearable data access.

Question 4

What are the costs after implementation?

Accepted Answer

Ongoing costs include infrastructure (hosting, database storage — typically $50–500/month depending on scale) and optional LLM API costs if using AI features. No hidden fees. No per-user charges. No pricing tiers. The solution itself is free — you're only paying for the infrastructure you'd need anyway.

Question 5

Can you build proprietary algorithms on top of Open Wearables?

Accepted Answer

Absolutely. The platform provides normalized, time-series health data in a consistent format across all wearable devices, creating the foundation for your proprietary algorithms and AI models. Instead of spending months on data cleaning and integration, you get clean, structured data ready for machine learning from day one. Teams are building personalized recovery scores, training readiness indicators, stress detection algorithms, sleep quality predictions, and custom health insights.

Question 6

Where is user data stored?

Accepted Answer

Data lives on your infrastructure. Open Wearables is self-hosted, which means you control where data goes, who can access it, and how long it's retained — it never flows through our servers. The platform always runs on your servers, not ours. For HIPAA or GDPR compliance, this matters because you can demonstrate complete data lineage without third-party data processing agreements.

Question 7

How can I test Open Wearables before connecting real devices?

Accepted Answer

Deploy Open Wearables locally using Docker. The platform includes sample data generation scripts that populate realistic health data — just run 'make seed' to seed synthetic user data and test your integration without connecting actual wearables. For Apple Health testing, you'll need physical iOS devices since HealthKit doesn't work in simulators.

Question 8

Can you access historical data from before the integration point?

Accepted Answer

Yes, but it depends on the provider. Apple Health supports full historical synchronization through the Flutter SDK. Garmin provides recent data by default, with historical access depending on your developer agreement. Other providers vary — most support some level of historical backfill through their APIs. For new users connecting wearables, historical data means they see immediate value instead of starting from zero.

Question 9

How does data deduplication work with multiple devices?

Accepted Answer

Open Wearables collects data from all connected sources. Deduplication happens when multiple devices report the same metric for the exact same timestamp. The platform resolves duplicates using configurable priority rules at two levels: device-type priority (smartwatch > phone > other devices) and provider priority (choose between providers when device types match). You configure these rules in your Open Wearables instance.

Question 10

Can you write data back to wearables?

Accepted Answer

No. Open Wearables currently operates as read-only, meaning you can pull health data from wearables but not write data back to them. This covers the majority of health app use cases: tracking metrics, analyzing patterns, providing coaching insights, and building personalized recommendations. Write capabilities may change in future releases based on community demand. If your application specifically requires write functionality, you'll need to implement direct integrations with individual wearable APIs alongside Open Wearables.

Aspect	SaaS APIs	In-House	Open Wearables
First API call	Hours	Months	5 minutes
Health scores	Black box, no audit	Build yourself	Open algorithms
AI reasoning	Limited / varies	Build yourself	MCP + reasoning tools
Self-hosted	No	Yes	Yes
Source code	Proprietary	—	MIT license
Custom scoring	No	Yes	Full access
Compliance-ready	Varies	Build yourself	HIPAA-ready
Time to customize	Weeks/never	Weeks	Hours
Debugging	Guess & wait for support	Internal team	Source code + community
Support	Slow, impersonal	Internal team	Community + core maintainers

Aspect	SaaS APIs	In-House	Open Wearables
First API call	Hours	Months	5 minutes
Health scores	Black box, no audit	Build yourself	Open algorithms
AI reasoning	Limited / varies	Build yourself	MCP + reasoning tools
Self-hosted	No	Yes	Yes
Source code	Proprietary	—	MIT license
Custom scoring	No	Yes	Full access
Compliance-ready	Varies	Build yourself	HIPAA-ready
Time to customize	Weeks/never	Weeks	Hours
Debugging	Guess & wait for support	Internal team	Source code + community
Support	Slow, impersonal	Internal team	Community + core maintainers

Health intelligence,
not just health data.

Data to decisions.
One platform.

Wearable Data

Health Scores

Health AI Engine

Coaching Profiles

Open algorithms.
Zero black boxes.

AI that reasons.
Not AI that reads.

Built for teams
that ship health products.

Enterprise

Corporate wellness

Clinical monitoring

AI coaching

Longevity and health optimization

Personal health

The table your CTO
will screenshot.

The people behind
the platform.

Bartosz Michalak

Sebastian Kalisz

Filip Begiełło

Anna Zych

Jakub Czajka

Grzegorz Sztuczyński

Kacper Gąsior

Kamil Piekarz

Need custom features built on top of Open Wearables?

Two ways to run
Open Wearables.

For developers

For companies

Stop building
the data layer.

Health intelligence, not just health data.

Data to decisions.One platform.