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Saylor Innovations Data Desk – Text Entity Extractor
x402
Saylor Innovations Data Desk – Text Entity Extractor is a paid API for AI agents from saylorinnovations.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-27).
Extracts structured entities (emails, URLs, IPs, phone numbers, money, dates, hashtags, mentions, crypto addresses, UUIDs, and more) from a given text string
Price / call$0.01
Success—
StatusUnknown
How this service works
Extract emails, URLs, IPs, phone numbers, money, percentages, dates, hashtags, mentions, EVM, Bitcoin and Solana-style addresses and UUIDs from text
Output
A JSON object containing a total entity count, a breakdown of counts per entity type (emails, URLs, phones, IPv4, dates, times, money, percentages, hashtags, mentions, hex colors, UUIDs, EVM addresses, Bitcoin addresses, Solana-like addresses), and a detailed entities object listing all discovered values per type. An optional note field may provide caveats about result interpretation.
Example use cases
Harvest contacts from scraped web content
“I just scraped a raw block of text from a company's about page — can you pull out every email address and phone number in it? Here's the text: 'Reach our sales team at sales@widgetco.com or call +44 20 7946 0958. For billing, email billing@widgetco.com.'”
Detect crypto addresses in on-chain message
“Someone posted a message in our Discord and I want to know if it contains any Ethereum, Bitcoin, or Solana wallet addresses — here's the raw message: 'Send your donation to bc1qar0srrr7xfkvy5l643lydnw9re59gtzzwf5mdq or 0xAbCd1234EF5678abcd1234ef5678ABCD1234ef56.'”
Extract dates and deadlines from a contract
“Pull out all the dates, times, and money amounts mentioned in this contract excerpt so I can build a timeline: 'Payment of $12,500.00 is due on March 15, 2025, with a 5% late fee applied after April 1, 2025 at 11:59 PM.'”
Technical details
Endpoint
GEThttps://saylorinnovations.com/api/text/entities?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to extract multiple heterogeneous entity types from a single text in one call, especially when the text may contain crypto wallet addresses (EVM, Bitcoin, Solana) alongside conventional contact data. It is ideal for processing unstructured text from emails, social posts, contracts, or logs where you don't know in advance which entity types are present. Prefer it over building custom regex pipelines or calling multiple specialized extractors separately.
Side effects
- Text shorter than 5 characters or longer than 5000 characters returns a validation error
- Ambiguous or malformed patterns (e.g. partial phone numbers) may be silently omitted
- Some entity types may return null counts if none were found, rather than zero
- Payment failure (x402) if USDC balance is insufficient
- False positives possible for loosely formatted entities like dates or money amounts
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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