Production-grade infrastructure for longitudinal health data.
102 API endpoints. 620+ health taxonomy nodes. Multi-source ingestion. Environmental enrichment. Insights engine. Built and operated by a 501(c)(3) nonprofit — which means the infrastructure is structurally aligned with your users, not against them.
The API
RESTful. Typed. Auditable.
The LLIF Data API covers the full lifecycle of longitudinal health data — from participant enrollment and event submission through compliance tracking, analytics, and program administration. 102 endpoints across 9 functional groups. OpenAPI specification available to approved partners.
https://api.dev.my.llif.org/data/redocAccess requires approved partner status. Request access via the Developer page.
Request API Access →The Data Model
620+ taxonomy nodes. One unified schema.
643 standardized schemas covering health, wellness, fitness, nutrition, symptoms, medications, mental health, and body metrics. Hierarchical classification enables cross-program and cross-study data harmonization — the same sleep event from one program can be correlated against nutrition data from another.
25+ weather, air quality, and pollen metrics are automatically attached to every health event by participant location and timestamp. Temperature, humidity, barometric pressure, AQI, PM2.5, PM10, NO2, O3, tree pollen, grass pollen, weed pollen, mold spores — the environmental context that makes population health correlations possible. No additional data collection required.
Every event is timestamped, typed, and stored against a participant record designed for long-term retention. The schema supports time-series queries, lagged correlations, and multi-year cohort analysis from day one. Data is not deleted at the end of a grant cycle or program period — it persists with participant consent.
Data gets in from everywhere participants already are.
Sync sources are modular. You can enable the sources relevant to your app or study and ignore the rest.
Analytics built in — not bolted on.
Correlation Analysis
Cross-series correlation across any two tracked variables — sleep quality vs. pollen count, exercise intensity vs. next-day mood, alcohol vs. sleep efficiency. Pearson correlations with confidence scoring. Available per participant and at aggregate (anonymous) level for program organizers.
Trend Detection
7-day, 30-day, and 90-day moving averages. Rate-of-change detection. Anomaly flagging for values outside personal historical range. Delivered as structured data to your app — you control how it's displayed.
Calendar Pattern Analysis
Hour-of-day, day-of-week, week-of-month, month-of-year, and lunar cycle distributions. Identifies recurrent patterns in health events — the weekend sleep spike, the Monday migraine, the spring allergy season start date — per participant.
ML-Based Predictions
Event occurrence probability, intensity range forecasting, and likelihood-weighted contributing factor identification. Models are trained per participant on their own longitudinal data. Predictions include confidence scores and are only surfaced after sufficient data volume is established.
Compliance tracking is infrastructure, not an add-on.
Plans define data collection schedules, targets, and conditions for any program. The platform tracks compliance automatically — confirming submissions through any input method (sync, manual entry, voice, barcode). Compliance records are timestamped, auditable, and available via API.
For research programs, this means IRB-reportable compliance data without manual reconciliation. For commercial programs, it means participant engagement metrics without building your own tracking layer.
Built to be trusted long-term.
Infrastructure decisions that look unusual from a commercial perspective — nonprofit structure, donor-restricted data, immutable consent records — are load-bearing trust signals for the participants your apps depend on.
Nonprofit GovernanceActive
Participant data is classified as a donor-restricted asset. Cannot be sold, monetized, or transferred in an acquisition. Survives bankruptcy. Requires IRS notification to modify. This is law, not policy.
IRB-Compatible ConsentActive
Participant opt-in consent architecture designed for IRB requirements. Clear data access boundaries, consent audit trails, and transparent handling. Consent records are immutable and timestamped.
HIPAA AlignmentIn Progress
Infrastructure designed for HIPAA-adjacent workloads. Encryption at rest and in transit. Access logging and audit trails. Full HIPAA Business Associate Agreement available for qualifying partners.
SOC 2 Type IIRoadmap
Certification planned. Current infrastructure follows SOC 2 principles: access controls, monitoring, incident response, and availability commitments.