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Studio Extract — Structured Field Extraction from Text
x402
Studio Extract — Structured Field Extraction from Text is a paid API for AI agents from short.desknav.ai, paid per call via x402, $0.15/call, status unknown (last checked 2026-09-14).
Extracts specified named fields from arbitrary text using an AI model, paid per-call in USDC via x402 on Base.
Price / call$0.15
Success—
StatusUnknown
How this service works
Studio sells 6 per-call jobs over HTTP, paid in USDC on base via x402 or direct transfer.
Output
Returns a JSON object with a 'result' containing the extracted field values as produced by the AI model, plus the model ID used, the offer ID ('extract'), an invoice ID for the payment transaction, and an input threat level assessment. Status is 'delivered' on success.
Example use cases
Invoice data extraction for accounting
“Pull out the vendor name, invoice date, and total due from this invoice text: 'Global Supplies Inc. sent invoice #8821 dated April 3, 2025 for $1,850 in office materials.'”
Resume parsing for HR screening
“Extract the fields 'candidate_name', 'years_of_experience', and 'most_recent_employer' from this resume snippet: 'Jane Doe has 8 years of software engineering experience. Her most recent role was at Stripe, where she led the payments infrastructure team.'”
News article fact extraction
“From this article excerpt, extract 'event_name', 'location', and 'date': 'The Annual Tech Summit will take place in San Francisco on June 10, 2025, drawing over 5,000 attendees from across the industry.'”
Technical details
Endpoint
POSThttps://short.desknav.ai/jobs/extractWhen to prefer
Choose this endpoint when you need to extract specific named fields from unstructured text programmatically, especially within an autonomous agent workflow that handles its own USDC micropayments via x402. It is well-suited for document parsing, entity extraction, and data structuring tasks where you define exactly which fields to pull. Prefer it over general-purpose LLM calls when you want a pay-per-use, invoice-tracked extraction with a defined schema response.
Side effects
- Missing required 'text' field returns a validation error
- Empty or very short text may yield incomplete or empty extractions
- Ambiguous field names may result in incorrect or null extractions
- Payment failure via x402 prevents job execution
- Model unavailability may delay or fail the response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| textrequired | string | The text to work on. |
| fields | array | Names of the fields to extract from the text. |
Output
Schema · Response
{
"output": {
"model": "<id of the model that ran the job>",
"result": "<the completed work>",
"offerId": "extract",
"inputThreatLevel": "low"
},
"status": "delivered",
"offerId": "extract",
"invoiceId": "inv_1"
}Tags
x402
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