Integrating Health and Wellness Data for Smarter Apps

The wearable market is expected to reach $186 billion by 2030. That's a lot of Fitbits, Apple Watches, Garmins, and Oura Rings your users expect to connect to your app. They don't care how complicated that is on your end.

For product teams, this creates a familiar tension. Users want broad device support, while engineering wants to ship features and not need to maintain integrations for 12 different devices.

The teams that move fastest aren't building these integrations from scratch. They're using unified APIs that handle the complexity for them.

The baseline has changed

The launch of ChatGPT Health and Claude for Healthcare in 2026 reset expectations for wellness data integration. OpenAI partnered with b.well to pull wearable data, Apple Health metrics, and nutrition apps directly into conversational AI, enabling users to query their fitness data in a language that is natural to them.

If a general-purpose assistant can integrate data from multiple wellness sources, specialized fitness and nutrition apps need to match and differentiate on top of that.

Why does integration work compound

Each wearable manufacturer provides their own SDK with distinct authentication, data formats, and rate limits. A typical wellness product might need Apple HealthKit for iOS, Health Connect for Android, plus direct integrations with Garmin, Fitbit, Whoop, and Oura.

API versions change, requiring ongoing maintenance. Technical debt accumulates fast, pulling engineering resources from core product work.

Then there's normalization. Heart rate from an Apple Watch arrives in different units and sampling intervals than heart rate from a Garmin. Sleep stages use different classifications. Without normalization, you can't build features that behave consistently, and your QA burden grows with every device you add.

Three integration approaches

When it comes to integrating wearables, you have three choices.

1. Direct device integration. This option gives you maximum control: own auth, retrieval, and storage. This approach works best if you're building exclusively within one ecosystem. The cost is 4-8 weeks per device, plus ongoing maintenance when APIs change.
2. Platform aggregators. Using HealthKit and Health Connect as local aggregators of user devices reduces complexity, but you're limited to the data users have already synced. Some device-specific metrics aren't exposed, and you will still need separate iOS and Android implementations.
3. Unified API. A unified provider handles device integrations, normalization, and maintenance. You will integrate once and receive data from numerous devices. Some providers support hundreds of wearables, and this is where most teams are moving.

OuiLive cut support tickets by 40% after switching to Spike API. Normalized data eliminated device-specific edge cases and delays that caused user complaints in their corporate wellness challenges.

What to evaluate

If you decide to go with a Wearables API, there are a few things to consider. 

Device coverage. Verify the API supports devices your users actually own. While fitness apps need Fitbit, Apple Watch, Garmin, Whoop, and Oura, weight management platforms might prioritize smart scales and nutrition integrations.

Normalization. Check whether the API normalizes units, timestamps, and sampling rates. This determines how much transformation logic you'll build yourself.

Sync modes. Some products need real-time workout data, while others need months of sleep history. Confirm that the provider supports both webhooks and historical backfills.

AI-ready outputs. If AI coaching is on your roadmap, your data pipeline should output formats that models can consume directly. Ideally, this would be taken care of by the API provider as MCP integrations are emerging as a standard for connecting wellness data to AI applications.

Timeline comparisons

Building direct integrations takes around 4-8 weeks per device for production-quality implementations. Multiply by the number of devices on your roadmap, and you are quickly looking at a year’s worth of work.

Unified APIs compress this. Built With Science, a fitness app with millions of users, completed its wearable integration in weeks. Their engineering team stayed focused on training algorithms instead of device SDKs.

Longevo achieved 15% higher engagement through wearable integrations, the kind of lift that's hard to hit when engineers are debugging OAuth across six manufacturers.

In essence, apps that use a unified API platform rather than building in-house ship faster and have less maintenance burden.

The full picture

Winning health, fitness, and wellness apps go beyond wearable integration. They also pull nutrition data or offer in-app features, body composition from smart scales, and recovery insights from sleep trackers.

The best APIs now cover wearables, nutrition scanning, and connected devices through a single integration point, reducing the number of vendor relationships and SDKs your team manages.

Spike Wearable API connects to 500+ devices across these categories. To see how it maps to your product requirements, book a demo.