# NetIntel Entity Extraction

> NetIntel Entity Extraction is a paid API for AI agents from netintel-production-440c.up.railway.app, 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 scored, graded result

## Facts

- Endpoint: POST https://netintel-production-440c.up.railway.app/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-extraction-eb298804
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_QZQflTGONlkpmtq-a2KzX

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-extraction-eb298804 -d '<json body>'
```

Example prompt: Extract all the named entities from this text — people, companies, locations, dates, emails, URLs, money amounts, and products — and give me a quality grade: 'Acme Corp announced that Jane Doe will lead operations from San Francisco starting 2024-03-15, with a $1.2M budget. Contact jane@acme.com or visit https://acme.com.'

## When to prefer this

Use this endpoint when you need structured named entity recognition with a quality score and letter grade from unstructured text. Prefer it over generic NLP pipelines when you need multi-type entity extraction (people, orgs, locations, dates, emails, URLs, money, products, phones) in a single call with pay-per-use micropayment pricing rather than a subscription.

## Known failure modes

- Empty or missing text body returns no entities with a low score
- Extremely short or single-word inputs may yield no extractable entities
- Non-English text may result in reduced accuracy or empty entity lists
- Malformed request body causes a 400-level error
- Payment failure via x402 prevents endpoint access entirely

## 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

A JSON object containing a letter grade (e.g. 'A') and numeric score (0–100) reflecting extraction confidence, a breakdown of entities by type (person, organization, location, date, email, url, money, product, phone), a findings array for any notable flags, and a total_entities count with a list of types_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-extraction-eb298804/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from netintel-production-440c.up.railway.app](https://www.zero.xyz/host/netintel-production-440c.up.railway.app/llms.txt)