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DataVault Extract — AI-Powered Text Entity Extraction
x402
DataVault Extract — AI-Powered Text Entity Extraction is a paid API for AI agents from zetavault.vercel.app, paid per call via x402, $0.03/call, status unknown (last checked 2026-09-15).
Extracts structured entities and data points from unstructured text using AI-powered NLP processing
Price / call$0.03
Success—
StatusUnknown
How this service works
54 endpoints spanning local tools, live data feeds, and AI-powered text processing. Pay-per-call with USDC on Base.
Output
Returns a JSON object with a 'data' field containing the extracted entities as structured key-value pairs, and a 'success' boolean indicating whether extraction completed successfully. The shape of 'data' reflects the entity types requested.
Example use cases
Example prompt
“Extract all the people names, organizations, and dates from this text: 'On March 5th, Elon Musk and Tim Cook met at Apple's headquarters in Cupertino to discuss a new partnership agreement.'”
Technical details
Endpoint
POSThttps://zetavault.vercel.app/api/extractWhen to prefer
Choose this endpoint when you need to extract structured entities or data points from raw, unstructured text and want a pay-per-call model without subscription overhead. Particularly useful for one-off or low-volume extraction tasks where spinning up a dedicated NLP pipeline isn't justified.
Side effects
- Missing required 'text' field returns validation error
- Empty string input may return empty data object with success:true
- Unsupported or malformed entity types in the array may be silently ignored
- Very long text inputs may hit payload size limits
- Network or server errors on the Vercel deployment may return 5xx responses
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| textrequired | string | |
| entities | array |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| data | object | |
| success | boolean |
Tags
x402
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