# DataVault Text Entity Extractor

> DataVault Text Entity Extractor is a paid API for AI agents from zetdatavault.vercel.app, paid per call via x402, $0.03/call, status unknown (last checked 2026-09-14).

Extracts named entities and structured data from unstructured text using AI-powered NLP processing

## Facts

- Endpoint: POST https://zetdatavault.vercel.app/api/extract
- Price: $0.03/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/datavault-text-entity-extractor-d3a98985
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_w9QrvJf3EsK51_fQvmtJa

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability datavault-text-entity-extractor-d3a98985 -d '<json body>'
```

Example prompt: Extract all named entities — people, organizations, dates, and locations — from this text: 'On March 5th, Elon Musk announced that Tesla would expand into Singapore, partnering with local firm GreenTech Solutions.'

## When to prefer this

Choose this endpoint when you need to extract named entities or structured data from free-form text and want a pay-per-call model without a subscription. Useful for one-off document processing, enriching records with entity data, or building pipelines that need NLP extraction without managing your own models. At $0.03 per call it is cost-effective for moderate volumes.

## Known failure modes

- Missing required 'text' field returns validation error
- Empty string input may return empty entity set with success=true
- Malformed JSON body returns 400 error
- Very long text may hit processing limits
- Invalid 'entities' array format causes schema validation failure
- Payment failure via x402 protocol returns 402 Payment Required
- Ambiguous entity types in the entities array may yield incomplete extraction

## 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 'success' boolean and a 'data' object containing the extracted entities organized by type, derived from the input text using AI-powered entity recognition.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "required": [
  "text"
 ],
 "properties": {
  "text": {
   "type": "string"
  },
  "entities": {
   "type": "array"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "data": {
   "type": "object"
  },
  "success": {
   "type": "boolean"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/datavault-text-entity-extractor-d3a98985/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from zetdatavault.vercel.app](https://www.zero.xyz/host/zetdatavault.vercel.app/llms.txt)