Structure

Structured outputs you can trust

Define your expected format once. Every response matches your schema, every time.

JSON schema Validation Consistent outputs Audit-ready

Visual

Schema enforcement path

Prompt → provider → validator → structured JSON or retry.

01

Prompt with schema

Define expected JSON structure

02

AI provider responds

Raw text or JSON from model

03

Schema validation

JSON-schema enforcement

04

Decision point

Valid → return structured JSON

Invalid → retry or reject

05

Trace + replayable

Full request logged for debugging

Schema
structure: "product_card"
schema:
  type: object
  required: ["title", "price", "bullets"]
  properties:
    title: { type: "string" }
    price: { type: "number" }
    bullets: { type: "array", items: { type: "string" } }
on_invalid: "reject"
              
1

Define once

Store schemas and reuse them across workflows and providers.

2

Validate outputs

Responses are checked against your schema; invalid payloads retry or reject.

3

Log what shipped

Request logs include the final structured body for auditing and replays.

Output shape

Guaranteed

Clients always get the schema you define.

Recovery

Retry or reject

Choose how to handle invalid outputs.

Traceability

Logged

See the final structured payload in logs.

Scroll the lifecycle

01 · Define

Create JSON schemas for outputs your app consumes.

02 · Enforce

Validate responses; retry or reject on drift.

03 · Deliver

Return predictable objects to downstream systems.

04 · Audit

Log final payloads to trace what shipped.

Use cases

  • Product catalogs, pricing cards, or summaries that must stay consistent.
  • Guardrails for downstream parsers and renderers.
  • Governance where outputs need audit trails.

What’s unique

  • Schema validation tied to your workflows.
  • Integrates with streaming and failover.
  • Final payloads visible in request logs.

Programmatic access

Attach structured outputs to workflows or pass inline

POST https://api.modelriver.com/v1/ai
Authorization: Bearer mr_live_your_key

{
  "workflow": "product-extractor",
  "messages": [...]
}

// Response returns validated structured data:
{
  "data": {
    "name": "Widget Pro",
    "price": 49.99,
    "category": "Electronics"
  },
  "meta": { "structured_output": true }
}

Define JSON schemas in the console and attach them to workflows. Responses are validated automatically.

Make AI outputs production-ready

Pair schemas with streaming and webhooks to deliver predictable, live, and verifiable results.