ENTROPY.RIP Schema Transducer

x402

ENTROPY.RIP Schema Transducer is a paid API for AI agents from entropy.rip, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-14).

Transforms raw unstructured text content into structured, schema-enforced JSON using LLM Structured Outputs

Price / call$0.05

Seller volume →—

Success—

StatusUnknown

How this service works

Transform raw unstructured context into schema-enforced JSON using LLM Structured Outputs

Output

A JSON object that conforms exactly to the provided schema, populated with values extracted and inferred from the input unstructured content using LLM Structured Outputs. Fields are typed and validated against the schema.

Example use cases

Parse job posting into structured data

“I have a raw job posting I scraped from a website and I need it turned into structured JSON with fields like job_title, company, location, salary_range, required_skills, and employment_type. Here's the posting text: 'Acme Corp is looking for a full-time Senior Backend Engineer in Austin, TX. You'll need 5+ years with Python and AWS. Salary is $130k–$160k depending on experience.'”

Extract invoice details from email

“Can you pull the key details out of this email from a vendor and structure it as JSON with fields for vendor_name, invoice_number, due_date, line_items (array of description and amount), and total_amount? Here's the email body: 'Hi, please find attached invoice #4821 from BlueSky Supplies dated Nov 1st. You owe $240 for 4 reams of paper and $85 for printer ink, total $325, due by November 30th.'”

Structure medical intake form responses

“A patient filled out their intake form as a block of free-form text and I need it converted into structured JSON matching this schema: {"patient_name": "string", "date_of_birth": "string", "chief_complaint": "string", "current_medications": ["string"], "allergies": ["string"]}. Here's what they wrote: 'My name is Robert Chen, born March 4 1978. I've been having chest tightness for two days. I take metformin and lisinopril daily. I'm allergic to penicillin and sulfa drugs.'”

Technical details

Endpoint

POSThttps://entropy.rip/api/schema/transduce

When to prefer

Choose this endpoint when you have a known target JSON schema and raw unstructured text that needs to be shaped into it — ideal for parsing documents, emails, user inputs, or any natural language context into typed structured data. Prefer this over generic LLM calls when you need guaranteed schema conformance rather than freeform text output.

Side effects

Schema is invalid or malformed JSON — returns error indicating schema parse failure
Content is too long or exceeds token limits — may return truncation or context error
Schema fields cannot be inferred from the content — may return null/empty values for unmappable fields
Downstream LLM unavailable — returns 503 or timeout error
Payment not processed or insufficient USDC balance — returns 402 Payment Required

Input

Schema · Request body

Field	Type	Description
schema	object	schema
content	string	content

Output

Schema · Response

{
  "type": "json",
  "example": {
    "structured_data": {
      "extracted_name": "example"
    }
  }
}

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How this service works

Transform raw unstructured context into schema-enforced JSON using LLM Structured Outputs

Output

Example use cases

Parse job posting into structured data

Extract invoice details from email

Structure medical intake form responses

Technical details

Endpoint

POSThttps://entropy.rip/api/schema/transduce

When to prefer

Side effects

Schema is invalid or malformed JSON — returns error indicating schema parse failure
Content is too long or exceeds token limits — may return truncation or context error
Schema fields cannot be inferred from the content — may return null/empty values for unmappable fields
Downstream LLM unavailable — returns 503 or timeout error
Payment not processed or insufficient USDC balance — returns 402 Payment Required

Input

Schema · Request body

Field	Type	Description
schema	object	schema
content	string	content

Output

Schema · Response

{
  "type": "json",
  "example": {
    "structured_data": {
      "extracted_name": "example"
    }
  }
}