# 24K Labs Entity Extractor

> 24K Labs Entity Extractor is a paid API for AI agents from api.24klabs.ai, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-15).

Extracts structured entities (emails, URLs, IPs, phone numbers, hashtags, mentions, money amounts, dates) from raw text using regex-based pattern matching.

## Facts

- Endpoint: POST https://api.24klabs.ai/api/v1/entity-extract
- Price: $0.002/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/24k-labs-entity-extractor-68b040dd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_mGAcdPR0byA9-ZH8QjJ9j

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 24k-labs-entity-extractor-68b040dd -d '<json body>'
```

Example prompt: Can you extract all the emails, phone numbers, URLs, and dates from this text: 'Contact John at john@example.com or +1-800-555-0199, visit https://example.com, our meeting is on March 15, 2025'?

## When to prefer this

Choose this endpoint when you need fast, deterministic, regex-based extraction of common entity types from raw text without the overhead or cost of an LLM. Ideal for structured log parsing, contact info extraction from form submissions, or preprocessing text before further analysis. Prefer over NLP-heavy alternatives when speed and consistency matter more than handling ambiguous or conversational phrasing.

## Known failure modes

- Empty or whitespace-only input returns all empty arrays
- Very long text inputs may hit payload size limits
- Regex patterns may miss non-standard formats (e.g. internationalized phone numbers, non-English date formats)
- Malformed request body returns a 400 error
- Rate limiting or quota exceeded returns a 429 or error response

## How this service works

Regex-based entity extraction: pulls emails, URLs, IPv4 addresses, phone numbers, hashtags, mentions, money amounts, and dates out of raw text.

## Output

Returns a structured object mapping each entity type (emails, urls, ipv4, phones, hashtags, mentions, money, dates) to an array of matched strings found in the input text. Entity types with no matches return empty arrays.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "text": {
   "type": "string"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "total": 5,
  "entities": {
   "urls": [
    "https://x.io"
   ],
   "emails": [
    "ops@x.io"
   ],
   "mentions": [
    "@dev"
   ]
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/24k-labs-entity-extractor-68b040dd/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from api.24klabs.ai](https://www.zero.xyz/host/api.24klabs.ai/llms.txt)