# NetIntel Text-to-JSON

> 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

## Facts

- Endpoint: POST https://netintel-production-440c.up.railway.app/text-to-json
- 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-text-to-json-d8a9c2a3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_kcbK1lhxbnmseIMqnju3C

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-text-to-json-d8a9c2a3 -d '<json body>'
```

Example prompt: Take this company blurb — 'Acme Corp is a private firm founded in 2010 with about 250 employees and offices in San Francisco and London' — and convert it into structured JSON with fields for company name, employee count, public status, locations, and founding year, then grade how well the text matched the schema.

## When to prefer this

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.

## Known failure modes

- 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

## 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.

## Request schema (JSON Schema)

```json
{
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "type": "object",
 "properties": {
  "input": {
   "type": "object",
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "type": "string",
     "enum": [
      "POST"
     ]
    },
    "bodyType": {
     "type": "string",
     "enum": [
      "json",
      "form-data",
      "text"
     ]
    },
    "body": {
     "type": "object",
     "properties": {
      "text": {
       "type": "string",
       "description": "The unstructured prose to extract structured data from. Max 10000 words or 50KB."
      },
      "schema": {
       "type": "object",
       "description": "A map of field name → type token. Supported tokens: string, number, boolean, date, string[], number[], object. Max 50 fields. Each field is extracted from the text as the declared type; output keys are forced to exactly these field names."
      }
     },
     "required": [
      "text",
      "schema"
     ]
    }
   },
   "required": [
    "type",
    "method",
    "bodyType",
    "body"
   ],
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object",
     "properties": {
      "result": {
       "type": "object",
       "description": "The extracted data: keys are exactly the schema field names, values pulled from the text and cast to the declared types, unfindable fields null."
      },
      "fields_in_schema": {
       "type": "number",
       "description": "Number of fields in the schema."
      },
      "fields_populated": {
       "type": "number",
       "description": "Number of non-null fields in the output."
      },
      "fields_nulled": {
       "type": "number",
       "description": "Number of null fields in the output."
      },
      "schema_match": {
       "type": "boolean",
       "description": "True when the model's output keys were exactly the schema field names. False when code had to force-conform (strip extra / add missing) keys."
      },
      "cached": {
       "type": "boolean",
       "description": "True if served from the in-memory cache."
      },
      "score": {
       "type": "number",
       "description": "Quality score 0-100."
      },
      "grade": {
       "type": "string",
       "description": "Letter grade A-F."
      },
      "findings": {
       "type": "array",
       "items": {
        "type": "string"
       }
… (truncated)
```

## Response schema (JSON Schema)

```json
{
 "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
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/netintel-text-to-json-d8a9c2a3/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)