Generate synthetic data from JSON Schema
Create browser-local sample records from a JSON Schema for demos, QA fixtures, and API contract testing without using real customer data.
Open the tool, then paste the sample input below. Everything runs locally in your browser.
The problem
Teams often need realistic-looking payloads for testing, demos, and examples, but production data can contain personal or sensitive values. A schema-based generator lets you create representative records without copying real data.
Sample input
{
"type": "object",
"properties": {
"id": { "type": "string", "format": "uuid" },
"email": { "type": "string", "format": "email" },
"active": { "type": "boolean" }
},
"required": ["id", "email"]
}Expected output
{
"id": "8b6f1a34-418f-4d4c-b967-0a8f2d7fd921",
"email": "user@example.com",
"active": true
}How to do it
- Paste a JSON Schema.
- Choose the number of records to generate.
- Set optional-field behavior if available.
- Generate the sample data.
- Copy or download the fixture for tests.
Common mistakes
- Using real customer exports as seed data.
- Forgetting required fields when hand-writing examples.
- Generating too many records for a browser-based fixture.
- Assuming synthetic data validates business rules not present in the schema.
Related tools
FAQ
Is synthetic data the same as anonymized production data?
No. Synthetic data is generated from rules or schema shape and should not contain real user values.
Can I use generated records in automated tests?
Yes. They are useful as fixtures when your tests need structurally valid payloads.
Is the schema uploaded?
No. Generation runs locally in your browser.
Is my data uploaded anywhere?
No. This workflow runs locally in your browser unless you explicitly copy or share the result yourself.
This guide uses browser-local tooling. Avoid pasting production secrets unless you understand what the tool displays and shares.
Continue with adjacent browser-based tools for the same workflow.