Overview
Generate 1 to 50 rows of realistic-looking mock data - names, emails, phone numbers, addresses, and company names - picked from hardcoded lists of common first names, last names, street names, cities, and company word parts, then combined and randomized so no two generation runs look identical. Toggle which fields to include with checkboxes, view the result as a table, and export exactly the fields you enabled as either CSV (for spreadsheets or bulk imports) or JSON (for seeding a database or mocking an API response). All the data is entirely fictional and generated locally in your browser - no real personal information is involved or required, which makes it safe to use for populating test databases, demoing a UI with realistic-looking content, or generating sample rows for a tutorial. Runs entirely client-side.
Best for: Populating a test database with realistic rows
How to use this tool
- Choose which fields to include. Name, email, phone, address, and company can each be toggled on or off.
- Set the row count. Generate anywhere from 1 to 50 rows with the slider.
- Rows generate as a table. Realistic-looking data appears immediately using randomized name and address combinations.
- Export as CSV or JSON. Copy the result in whichever format your test setup needs.
Why use this tool
Choose exactly which fields
Toggle name, email, phone, address, and company independently - export only what you need.
Two export formats
Copy as CSV for a spreadsheet or bulk import, or JSON for seeding a database or mocking an API.
Entirely fictional data
Every row is randomly assembled - no real personal information is involved or required.
Up to 50 rows at once
Generate a realistic-sized test dataset in one pass instead of copy-pasting single rows.
Frequently asked questions
No - every field is assembled from combinations of common name parts, street names, and company word fragments, then randomized. The specific combinations (a given name paired with a given surname, address, and email) are generated fresh each time and don’t correspond to real individuals, though names and addresses may occasionally coincidentally resemble real ones simply because the underlying word lists are drawn from common, real-world naming conventions.
CSV is the right format for importing into a spreadsheet tool like Excel or Google Sheets, or for bulk-uploading rows into a system that expects tabular data. JSON is better suited for seeding a test database, mocking an API response in a frontend test, or feeding directly into JavaScript code that expects an array of objects - pick whichever matches what you’re about to paste the data into.