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NetIntel Text-to-JSON
x402
NetIntel Text-to-JSON 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).
Converts unstructured text input into validated, structured JSON output according to a schema, with grading and quality scoring
Price / call$0.05
Success—
StatusUnknown
How this service works
Turn unstructured text into structured JSON matching a caller-supplied schema using Claude Haiku — the agent declares the fields and types it wants, and gets back populated JSON with values pulled from the text and coerced to the right types, so agents can structure any prose into the exact shape their pipeline expects.
Output
Returns a graded JSON object containing: a letter grade (A–F), a numeric score (0–100), a cached flag, the structured result object with extracted fields, a schema_match boolean, count of nulled fields, total schema fields, and populated field count — plus a findings array noting any issues.
Example use cases
Parse job descriptions into recruitment templates
“I've got a stack of unstructured job postings from our careers page. Can you extract each one into a structured JSON with fields for job title, department, required skills, salary range, and location, then grade how complete each extraction is? I need to know which postings are missing critical info.”
Convert customer feedback into structured insights
“We're getting raw customer support tickets and need to turn them into structured data. Pull out sentiment, product mentioned, issue category, and requested feature from each ticket, convert it to JSON, and give me a quality score so I know which feedback is most complete and reliable.”
Extract vendor details from email pitches
“Sales keeps forwarding me vendor pitches as unformatted emails. Can you parse each one into structured JSON with company name, service offering, pricing model, target industry, and contact info? Grade each extraction so I know which vendors provided clear, complete information.”
Technical details
Endpoint
POSThttps://netintel-production-440c.up.railway.app/text-to-jsonWhen to prefer
Choose this endpoint when you need to convert freeform prose or natural language into a validated, schema-conformant JSON object and want a quality grade telling you how complete the extraction was. Ideal for ETL pipelines, data enrichment from unstructured sources, or when you need a confidence signal (grade + score) alongside the structured output. Prefer over generic LLM extraction when you need a consistent grading rubric and field-level completeness metrics.
Side effects
- Text too ambiguous to map to requested schema fields — low score and many nulled fields returned
- Schema mismatch when input text contains no relevant information — grade F or low
- Micropayment failure if x402 USDC payment on Base mainnet is not completed — 402 response returned
- Malformed input text or missing schema target — 400 bad request
- Service unavailability on Railway infrastructure — 503 or timeout
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"grade": "A",
"score": 100,
"cached": false,
"result": {
"company": "Acme Corp",
"employees": 250,
"is_public": false,
"locations": [
"San Francisco",
"London"
],
"founded_year": 2010
},
"findings": [],
"schema_match": true,
"fields_nulled": 0,
"fields_in_schema": 5,
"fields_populated": 5
}
}Tags
x402
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