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.

Schema · validate · retry

Prompt

with schema

Provider

raw text response

Validator

json-schema enforcement

Decision

Valid → structured JSON

Invalid → retry / reject

Logged

Trace + replayable

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.

Make AI outputs production-ready

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