# NetIntel Entity Extract API

> NetIntel Entity Extract API is a paid API for AI agents from netintel.dev, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-13).

Extracts named entities (persons, organizations, locations, dates, emails, URLs, money, products, phone numbers) from text and returns a graded structured result

## Facts

- Endpoint: POST https://netintel.dev/entity-extract
- Price: $0.05/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-13
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/netintel-entity-extract-api-5debcddb
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_XG4mPfyBGoppBd5X9UzMC

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 netintel-entity-extract-api-5debcddb -d '<json body>'
```

Example prompt: Extract all named entities from this press release text — I need the people, organizations, locations, dates, money amounts, emails, URLs, and products mentioned: 'Acme Corp CEO Jane Doe announced a $1.2M partnership with WidgetPro in San Francisco on March 15, 2024. Contact jane@acme.com or visit https://acme.com for details.'

## When to prefer this

Choose this endpoint when you need a graded, multi-type named entity extraction from free-form text in a single call, especially when you want people, orgs, locations, dates, emails, URLs, money, and products all identified together with a quality score. Prefer this over generic NLP libraries when you need a pay-per-call SaaS solution with no setup, or when building pipelines that need entity richness scoring alongside raw extraction.

## Known failure modes

- Empty or very short text input may return zero entities with a low score
- Text in unsupported languages may yield incomplete extraction
- Ambiguous or poorly formatted text may misclassify entity types
- Network or payment failure via x402 micropayment results in 402 Payment Required
- Malformed POST body returns 400 Bad Request

## How this service works

Extract named entities from text using Claude Haiku — people, organizations, locations, dates, emails, URLs, money amounts, and products — returned as structured typed arrays so agents can pull structured signals out of unstructured text in one call.

## Output

Returns a JSON object with an overall grade (e.g. 'A') and numeric score (0-100), a breakdown of extracted entities grouped by type (person, organization, location, date, email, url, money, product, phone), a list of findings, a total entity count, and the list of entity types that were extracted.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method",
    "bodyType",
    "body"
   ],
   "properties": {
    "body": {
     "type": "object",
     "required": [
      "text"
     ],
     "properties": {
      "text": {
       "type": "string",
       "description": "The text to extract named entities from — an article, email, document, or any unstructured text. Max 10000 words or 50KB."
      },
      "types": {
       "type": "array",
       "items": {
        "type": "string"
       },
       "description": "Optional subset of entity types to extract: person, organization, location, date, email, url, money, product, phone. Defaults to all types."
      }
     }
    },
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "POST"
     ],
     "type": "string"
    },
    "bodyType": {
     "enum": [
      "json",
      "form-data",
      "text"
     ],
     "type": "string"
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object",
     "properties": {
      "grade": {
       "type": "string",
       "description": "Letter grade A-F"
      },
      "score": {
       "type": "number",
       "description": "Quality score 0-100"
      },
      "entities": {
       "type": "object",
       "description": "Per-type arrays of unique entity strings as they appear in the text. Only requested types appear when the types param is supplied."
      },
      "findings": {
       "type": "array",
       "items": {
        "type": "object"
       },
       "description": "Informational findings (e.g. extraction errors)"
      },
      "total_entities": {
       "type": "number",
       "description": "Total count across all entity arrays"
      },
      "types_extracted": {
       "type": "array",
       "items": {
        "type": "string"
       },
       "description": "The entity types included in this response"
      }
     }
    }
   }
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "grade": "A",
  "score": 100,
  "entities": {
   "url": [
    "https://acme.com"
   ],
   "date": [
    "2024-03-15"
   ],
   "email": [
    "jane@acme.com"
   ],
   "money": [
    "$1.2M"
   ],
   "phone": [],
   "person": [
    "Jane Doe",
    "John Smith"
   ],
   "product": [
    "WidgetPro"
   ],
   "location": [
    "San Francisco"
   ],
   "organization": [
    "Acme Corp"
   ]
  },
  "findings": [],
  "total_entities": 9,
  "types_extracted": [
   "person",
   "organization",
   "location",
   "date",
   "email",
   "url",
   "money",
   "product",
   "phone"
  ]
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/netintel-entity-extract-api-5debcddb/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from netintel.dev](https://www.zero.xyz/host/netintel.dev/llms.txt)