What does the seed do?

The seed is the input to a deterministic pseudo-random generator. Given the same seed, the tool walks the exact same sequence of random choices, so it produces byte-for-byte identical users every time — same names, emails, addresses, everything. Change the seed (or click Regenerate, which picks a new random seed) and you get a completely different but equally stable set. This is what makes the output reproducible across machines and safe to rely on in tests.

Is the generated data real or does it belong to anyone?

It is entirely synthetic. Names are drawn from common first/last name pools, emails are constructed from those names, addresses combine random street numbers with real city and region names, and phone numbers follow each country format but are not assigned to anyone. None of it maps to a real person. It is meant for testing and demos — do not use it to imply real individuals, and never use it where genuine, verified data is required.

Which export format should I use?

Use JSON for general-purpose fixtures and API mocks. NDJSON (newline-delimited JSON) is ideal for streaming or bulk-importing into databases and log pipelines that read one record per line. CSV opens directly in spreadsheets. SQL produces an INSERT statement you can drop into a seed script. TypeScript gives you a typed const you can import straight into code. All formats honor the fields you selected, so you only get the columns you want.

Does the locale change anything besides names?

Yes. Each locale switches the first and last name pools, the cities and regions, the street-suffix style, the phone-number format, the postcode format, and the email top-level domain (for example .co.uk for the UK). So a UK locale yields British names, London-area cities, 07 mobile numbers, and UK-style postcodes, while the German locale uses German names, cities, and street conventions. This keeps your test data internally consistent for the country you are targeting.

How are the avatars generated, and do they require a network call?

The avatar field is a URL pointing at the DiceBear avatar service, generated deterministically from each user id and the style you pick (Avataaars, Bots, Personas, Thumbs, or Initials). The profile data itself is created entirely in your browser with no network requests; only displaying the avatar image in the preview (or wherever you ultimately render the URL) fetches it. If you do not need avatars, simply untick the avatar field and the URLs are omitted from the output.

Can I generate more than 100 users?

The interface caps the count at 100 to keep the live preview responsive, and the preview itself shows the first 12 while the full set goes to the export. The underlying engine can produce up to 1000 in a single call, so if you need a larger batch you can drive it programmatically or run the tool a few times with different seeds. For most seeding and testing needs, a few dozen reproducible records is plenty.

Random User Generator

Generate realistic, reproducible fake user profiles for testing and seeding databases. A named seed makes every run deterministic and shareable — the same seed always yields the same users. Pick a locale, gender, and avatar style, choose exactly which fields you want, then export to JSON, NDJSON, CSV, SQL, or TypeScript.

About this ToolHow it works, benefits & use cases

Generate realistic fake user profiles for testing, demos, and database seeding — but with a twist most generators lack: it is fully reproducible. Every run is driven by a named seed, and the same seed always produces exactly the same users. That means you can commit a fixture, paste a shareable URL into a ticket, or write a test that asserts on specific values, and get identical output every time, on every machine. Pick how many users you want (up to 100 in the UI), choose a locale so names, cities, phone numbers, and postcodes look right for that country (US, UK, France, Germany, or Brazil), select a gender bias, and choose an avatar style. Then tick exactly which fields you need — id, name, email, username, avatar, gender, date of birth, age, phone, address, company, bio, website — and export to JSON, NDJSON (one object per line, perfect for bulk imports), CSV for a spreadsheet, a SQL INSERT statement for a seed script, or a TypeScript const for an in-code fixture. A live card preview shows the first dozen profiles as you tune the options, and the whole configuration is captured in the URL.

How to Use

1Set a seed (any text) — the same seed always regenerates the same users — or hit Regenerate for a fresh set.
2Choose how many users, a locale, a gender bias, and an avatar style.
3Tick exactly the fields you want in the output, or use the All / Minimal shortcuts.
4Pick an export format: JSON, NDJSON, CSV, SQL INSERT, or TypeScript.
5Copy or download the output, or share the URL so a teammate gets the identical dataset.

Key Benefits

Seeded and reproducible: the same seed always yields the same users
Locale-aware names, cities, phone formats, and postcodes (US, UK, FR, DE, BR)
Choose exactly which fields appear in the output
Exports to JSON, NDJSON, CSV, SQL INSERT, and TypeScript
Live card preview of the generated profiles
Deterministic output is safe for snapshot tests and shareable via URL
Runs entirely in your browser — no data leaves your machine

Common Use Cases

Seeding a development or staging database with believable users
Creating stable fixtures for unit and integration tests
Filling a UI prototype or design mockup with realistic content
Generating CSV or SQL sample data for a demo or tutorial
Producing a shareable, reproducible dataset for a bug report

Preview5

Ava Harris
[email protected]
Austin
HR Manager
Linda Walker
[email protected]
San Diego
Sales Director
Richard Clark
[email protected]
San Diego
Project Manager
Lucas Harris
[email protected]
New York
Sales Director
Robert Lopez
[email protected]
Detroit
Product Manager

Seed consolelog — same seed, same people.

Generation

Seed

Any text — drives reproducibility

Count

Gender

Locale

Avatar

Fields

Output format

JSON output

Copy, download, share, or pipe to another tool

[
  {
    "id": "1305b25a-966d-4805-82bd-ca03f196d51d",
    "firstName": "Ava",
    "lastName": "Harris",
    "fullName": "Ava Harris",
    "email": "[email protected]",
    "username": "avaharris",
    "avatar": "https://api.dicebear.com/7.x/avataaars/svg?seed=1305b25a-966d-4805-82bd-ca03f196d51d",
    "gender": "female",
    "dateOfBirth": "1999-11-22",
    "age": 27,
    "phone": "(283) 485-4049",
    "address": {
      "street": "6843 Jackson Ln",
      "city": "Austin",
      "state": "New York",
      "country": "United States",
      "zipCode": "34061"
    },
    "company": {
      "name": "Blockchain Systems",
      "position": "HR Manager",
      "department": "Engineering"
    },
    "bio": "Passionate about technology and innovation. Love to solve complex problems.",
    "website": "https://avaharris.com"
  },
  {
    "id": "065ab0ec-7fa8-43f9-a59b-55f2f116db12",
    "firstName": "Linda",
    "lastName": "Walker",
    "fullName": "Linda Walker",
    "email": "[email protected]",
    "username": "linda39",
    "avatar": "https://api.dicebear.com/7.x/avataaars/svg?seed=065ab0ec-7fa8-43f9-a59b-55f2f116db12",
    "gender": "female",
    "dateOfBirth": "1959-04-06",
    "age": 67,
    "phone": "(484) 599-1581",
    "address": {
      "street": "1227 White Blvd",
      "city": "San Diego",
      "state": "Oklahoma",
      "country": "United States",
      "zipCode": "45225"
    },
    "company": {
      "name": "AI Research Lab",
      "position": "Sales Director",
      "department": "Customer Support"
    },
    "bio": "Experienced professional with a focus on delivering quality results.",
    "website": "https://lindawalker.com"
  },
  {
    "id": "112e0ca8-d477-4e03-9a54-7dfb5bba0d65",
    "firstName": "Richard",
    "lastName": "Clark",
    "fullName": "Richard Clark",
    "email": "[email protected]",
    "username": "richardclark",
    "avatar": "https://api.dicebear.com/7.x/avataaars/svg?seed=112e0ca8-d477-4e03-9a54-7dfb5bba0d65",
    "gender": "male",
    "dateOfBirth": "1961-08-08",
    "age": 65,
    "phone": "(951) 824-9397",
    "address": {
      "street": "4401 Robinson Ave",
      "city": "San Diego",
      "state": "Michigan",
      "country": "United States",
      "zipCode": "82360"
    },
    "company": {
      "name": "Digital Innovations",
      "position": "Project Manager",
      "department": "Marketing"
    },
    "bio": "Experienced professional with a focus on delivering quality results.",
    "website": "https://richardclark.com"
  },
  {
    "id": "7980677d-5d96-40c1-ba4c-0642c0c7bd3c",
    "firstName": "Lucas",
    "lastName": "Harris",
    "fullName": "Lucas Harris",
    "email": "[email protected]",
    "username": "lucas_harris",
    "avatar": "https://api.dicebear.com/7.x/avataaars/svg?seed=7980677d-5d96-40c1-ba4c-0642c0c7bd3c",
    "gender": "male",
    "dateOfBirth": "1959-03-17",
    "age": 67,
    "phone": "(943) 807-9047",
    "address": {
      "street": "7645 Rodriguez Dr",
      "city": "New York",
      "state": "Maine",
      "country": "United States",
      "zipCode": "29138"
    },
    "company": {
      "name": "Future Technologies",
      "position": "Sales Director",
      "department": "Design"
    },
    "bio": "Team player with excellent communication skills.",
    "website": "https://lucasharris.com"
  },
  {
    "id": "0af92b10-43f5-4de3-a760-15f35225fff6",
    "firstName": "Robert",
    "lastName": "Lopez",
    "fullName": "Robert Lopez",
    "email": "[email protected]",
    "username": "robert38",
    "avatar": "https://api.dicebear.com/7.x/avataaars/svg?seed=0af92b10-43f5-4de3-a760-15f35225fff6",
    "gender": "male",
    "dateOfBirth": "1981-06-13",
    "age": 45,
    "phone": "(673) 244-1731",
    "address": {
      "street": "2342 Lee Way",
      "city": "Detroit",
      "state": "North Carolina",
      "country": "United States",
      "zipCode": "53517"
    },
    "company": {
      "name": "Global Systems",
      "position": "Product Manager",
      "department": "Marketing"
    },
    "bio": "Experienced professional with a focus on delivering quality results.",
    "website": "https://robertlopez.com"
  }
]

Reproducible by design

Unlike most fake-data tools, this one is built on a seeded random generator. The same seed always produces the same users, so you can commit a fixture, share a URL, or write a test that expects exact values — and get identical output every time. Change the seed (or hit Regenerate) for a fresh, equally-stable set.

Built for seeding and tests

Pick only the fields you need, choose a locale so names, cities, and phone formats match, and export straight to SQL for a seed script, CSV for a spreadsheet, NDJSON for a bulk import, or TypeScript for an in-code fixture.

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Random User Generator

How to Use

Key Benefits

Common Use Cases

Generation

Fields

Reproducible by design

Built for seeding and tests

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Frequently Asked Questions - Random User Generator