Schema To Runtime API

Stop waiting on backend. Ship with realistic data now.

Define your schema (or prompt AI), generate seeded relational data, and connect your frontend to live CRUD endpoints in minutes.

  • Model schemas visually or generate them with AI
  • Create seeded relational datasets that regenerate predictably
  • Ship frontend flows against live CRUD endpoints immediately

Free plan includes 1 project, 1 source, and up to 10,000 rows.

Mock data helps you design screens. It doesn’t help you ship flows

The issue is not missing data. It is missing consistency between what your frontend expects and what your backend eventually delivers.

Why it matters

The hidden cost of placeholder data

  • Velocity drops: UI and backend integration work happens twice.
  • QA confidence drops: failed scenarios are hard to replay exactly.
  • Demo quality drops: product screens look convincing, interactions do not.

Problem 01

Fixtures drift quickly

Static JSON rarely matches real product behavior once flows get complex.

Result: growing mismatch between design QA and runtime behavior.

Problem 02

Backend timelines block frontend

UI delivery slows down when API contracts and data are not ready yet.

Problem 03

QA data is hard to reproduce

Without deterministic seeds, bug scenarios are hard to recreate consistently.

How Synthbrew works

1

Model your schema

Use the schema editor or AI prompt flow, then keep immutable versions.

2

Generate and regenerate

Populate seeded relational data now, and regenerate with controlled defaults.

3

Integrate instantly

Connect your app with runtime CRUD API endpoints and source API keys.

Core capabilities in one platform

Built for a clean and practical workflow: schema design, data generation, runtime access, and team controls.

Schema modeling + immutable versions

Define tables and relationships once, then publish versions your sources can pin to.

  • Visual editing and AI-assisted schema creation
  • Version history with stable references
  • Per-source schema pinning for controlled changes

Schema editor preview

users

id, email, created_at

orders

id, user_id, total

subscriptions

id, user_id, status

Screenshot placeholder: replace with schema builder capture.

Entity distribution

Seeded generation control

Control row volume, locale, timezone, and seed so environments stay reproducible.

  • Deterministic regeneration with seeds
  • Per-entity row distribution

Generation controls

rowCount100,000
seeddemo-2026

Runtime API + key auth

Each source exposes CRUD endpoints and uses source-level API keys for runtime access.

  • GET, POST, PATCH, DELETE per table
  • `x-api-key` runtime authentication

Runtime endpoint

/api/runtime/:sourceId/:table

Team workflows

Collaborate with role-based access, invite links, and usage visibility.

  • Owner/admin/member permissions
  • Scoped invites with expiry and max uses
owneradminmemberscoped invite
Team invite

Optional read-only Postgres access

On supported plans, provision a dedicated read-only Postgres user for a source schema.

  • Dedicated credentials per source
  • Connection URL shown once on provision/rotation

Short product clip placeholder

Suggested: 6-10s read-only DB access walkthrough.

Product proof, not promises

Runtime API example

GET /api/runtime/{sourceId}/users
POST /api/runtime/{sourceId}/orders
PATCH /api/runtime/{sourceId}/orders/{id}
DELETE /api/runtime/{sourceId}/orders/{id}

Headers:
x-api-key: sb_src_********************************
View documentation

Generation event timeline

queued

Generation request accepted and waiting to run.

active

Schema compile + data seeding in progress.

success

Rows inserted and runtime namespace updated.

Runtime calls use x-api-key with source API keys.

Where teams use Synthbrew

Frontend delivery before backend completion

Ship product flows and polish UX while backend APIs are still in progress.

Reproducible QA/test environments

Regenerate known states with the same seed to reproduce and verify fixes.

Production-like demos

Show realistic data and interactions without hardcoding brittle mocks.

Why not just use static generators or JSON files?

CapabilitySynthbrewStatic data generators
Live CRUD endpointsBuilt in per sourceNot available
Seeded regenerationDeterministicManual reruns
Schema versioningImmutable versionsAd hoc
Team permissions + invitesRole-based and scopedUsually absent

Build with production-like data before production backend exists.

Start with a schema. Generate data. Integrate your frontend today.

Create your first source