Data from everywhere participants already are.
LLIF ingests from wearables, health platforms, manual entry, and environmental sources — so participants don't have to change how they live to generate valuable longitudinal data.
Wearables & health platforms
Sync integrations pull data from participants' existing devices and platforms automatically.
Apple Health
LiveThe primary iOS health data aggregator. Syncs activity, workouts, sleep, heart rate, HRV, steps, nutrition, body metrics, and any data written by other Apple Health connected apps including Oura, Whoop, and Garmin.
Google Health Connect
LiveAndroid health data platform. Syncs activity, workouts, sleep, heart rate, nutrition, and body metrics from Google Fit and connected Android health apps.
Fitbit
LiveDirect Fitbit integration. Syncs sleep stages, activity, heart rate, SpO2, skin temperature, HRV, and stress score.
Garmin
LiveDirect Garmin Connect integration. Syncs detailed workout data, GPS tracks, VO2 max estimates, sleep, heart rate, body battery, and stress.
Oura
LiveDirect Oura Ring integration. Syncs readiness score, sleep stages, HRV, resting heart rate, body temperature, and activity.
Whoop
LiveDirect Whoop integration. Syncs recovery score, strain, sleep performance, HRV, resting heart rate, and respiratory rate.
Manual & active entry
Not everything worth tracking comes from a wearable. LLIF supports multiple manual input methods so participants can log anything.
Direct Input
Structured manual entry for any of LLIF's 620+ taxonomy nodes — symptoms, medications, mood, notes, custom fields. Templates pre-fill common fields for speed.
Voice Logging
Log events by voice. Transcribed and parsed into structured event data automatically. Useful for on-the-go logging where manual typing is inconvenient.
Barcode Scan
Scan food and supplement barcodes for instant nutritional data lookup. Matched against the LLIF nutrition database with manual override available.
AI-Assisted Entry
AI template suggestions based on user context — if you logged a morning run yesterday, the system suggests it today. Pre-fills known fields from prior events. Reduces logging friction for repetitive tracking.
Manual entry endpoints: POST /v3/event/ with AI-driven template suggestions. Feed retrieval: POST /v3/event/feed/
Environmental enrichment
Attached automatically to every event — no participant action required.
Every health and lifestyle event logged to LLIF is automatically enriched with 25+ environmental metrics based on the participant's location and the event timestamp. Participants don't need to log environmental conditions — the platform attaches them.
Environmental enrichment is why LLIF is particularly powerful for allergy, respiratory, pain, and mood research — the environmental context is already there, attached to every data point.
On the roadmap
Continuous Glucose Monitor (CGM)
Direct integration with CGM devices for real-time glucose data. Enables correlation of glucose response against nutrition, activity, sleep, and stress.
Lab Results
Structured import of bloodwork and lab panel results. Manual upload and direct lab integration pathways in development.
Genomics
Integration with consumer genomics platforms for longitudinal correlation of genetic markers against tracked health and lifestyle outcomes.
DICOM / Medical Imaging
Structured metadata import from medical imaging studies — not image storage, but event-level records of imaging procedures and findings.
Building an integration?
Implementation details are in the developer docs.
If you're building an app on OpenLife Cloud and want to implement sync from a wearable or health platform, the integration layer is handled at the SDK and API level — not at the platform configuration level.
The /v3/event/ endpoints accept structured event data from any source. Wearable sync connectors are available as part of the LLIF SDK.