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Wellnizz Wearables Analyze
x402
Wellnizz Wearables Analyze is a paid API for AI agents from app.wellnizz.com, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-14).
Analyzes wearable device data to generate health findings, insights, and action plans based on activity, sleep, and biometric signals.
Price / call$0.05
Success—
StatusUnknown
How this service works
Wellnizz API and MCP-compatible service for genetics, biomarkers, wearables, lab discovery, dashboard specs, action plans, and hosted billing.
Output
Returns a JSON object with an analysis ID, a completion status, and a findings array containing health insights, flagged biomarker patterns, and potentially action plan items derived from the submitted wearable data.
Example use cases
Weekly fitness tracker health review
“Take my Fitbit data from the past 7 days — steps, heart rate, and sleep — and run a Wellnizz wearable analysis to tell me what health findings stand out and what I should be doing differently.”
Post-workout biometric assessment
“I just finished a hard training week. Can you send my Apple Watch biometric data to Wellnizz and analyze it for recovery status, any red flags in my heart rate variability, and give me action plan suggestions?”
Chronic condition wellness monitoring
“I have my continuous glucose monitor and smartwatch data from the last month. Can you run a Wellnizz wearables analysis on all of it and give me findings I can share with my doctor?”
Technical details
Endpoint
POSThttps://app.wellnizz.com/wearables/analyzeWhen to prefer
Choose this endpoint when you need to process raw or structured wearable device data and receive actionable health findings in return. It is part of the Wellnizz platform which combines genetics, biomarkers, and wearables — making it ideal when the user already has wearable data on hand and wants AI-driven interpretation rather than a generic fitness summary. Prefer this over generic data storage or dashboard APIs when the goal is analysis and recommendations, not just visualization.
Side effects
- Missing or malformed wearable data payload returns an error
- Unsupported wearable data format may result in empty findings
- Payment failure via x402 protocol blocks the request
- Incomplete biometric data sets may yield low-confidence or empty findings
- Service timeout if data volume is too large
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"id": "an_...",
"status": "complete",
"findings": []
}
}Tags
x402
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