Fake Data Generator
Spin up realistic but fictional people for test fixtures, demo screenshots, and Storybook props. Output as plain text, CSV, or JSON — all using the IETF-reserved example.com domain so emails never accidentally deliver.
One person as JSON, CSV, or text
All fictional, all using the safe example.com domain. Switch the format selector to match your downstream tool.
{
"name": "Maya Rodriguez",
"email": "maya.rodriguez@example.com",
"phone": "+1-415-552-3014",
"address": "182 Oak Ave, Lakewood, CA 94011",
"age": 34,
"job": "Designer"
}name,email,phone,address,age,job "Maya Rodriguez","maya.rodriguez@example.com","+1-415-552-3014","182 Oak Ave, Lakewood, CA 94011",34,"Designer"
What you'll use this for
Realistic-looking data without any privacy risk — no real people, no usable emails.
Test fixtures
Seed unit and integration tests with stable-looking customer rows.
Demo screenshots
Populate Figma or marketing site mockups with believable user lists.
Database seeding
Generate hundreds of rows for a dev database, exportable as SQL INSERT.
Load testing
Drive load tools (k6, Locust) with a payload of unique-looking users.
How to generate fake data
Pick a count
From 1 record for a quick sample to 1,000 for a load-test fixture.
Toggle fields
Only include name and email, or pile on phone, address, age, and job title.
Pick a format
JSON for code, CSV for spreadsheets, SQL for direct DB inserts, plain text for docs.
Copy or download
Use the action bar to copy or save with the right file extension.
Frequently asked questions
No. They all use the IETF-reserved example.com domain (RFC 2606), which will never be assigned to anyone, so mail sent there silently drops.
No. First and last names are picked uniformly at random from common English-language name lists, then combined; addresses, phones and jobs are randomly assembled.
Yes. Use the format selector — JSON for code, CSV for spreadsheets, plain text for documentation, or SQL INSERT for database seeding.
Possibly — the tool doesn't enforce uniqueness because that would require maintaining a global pool. For small counts (under a few hundred) collisions are rare; dedupe externally if you need guarantees.
Not yet — the name and address lists are English-language. For multi-locale fake data use a library like Faker.js in your own code.
About fake data for testing
Real customer data is a liability in dev environments — privacy regulations like GDPR, CCPA, and HIPAA forbid copying production records into staging. Synthetic data sidesteps the problem entirely while still exercising your code paths.
Safe by design
- example.com domain — RFC 2606 reserves it so no email will deliver.
- 555 phone prefix — North American fictitious-use prefixes prevent accidental dialing.
- Random street numbers — combined with random street + city, the addresses are almost certainly fictional.