Data Anonymizer

Data anonymization

Test data from a production export

Real data finds the bugs that made-up data does not, but it should not sit in a test system with real names in it. Pseudonymize the personal columns, shift the dates, and keep everything else as it is.

Drop a CSV or Excel file

Or click to choose. Up to 200 MB; the file is processed on this computer and never uploaded.

Relations survive

Process the customers file and the orders file with the same key file, and a customer's email becomes the same placeholder in both. Foreign keys that are personal data, such as an email used as a customer reference, still join.

Dates moved together

Shift dates moves every date by the same number of days, between one and 365, taken from the key. Intervals stay correct: an order placed three days after sign-up is still three days after it, and age and tenure calculations still work within a year.

Placeholder emails cannot be mailed

Pseudonymized email addresses end in example.invalid, a domain reserved so that it never receives mail. A test system that sends notifications cannot reach a real customer by accident.

Pricing

Free

$0

10,000 rows a month

Without an account: 1,000 rows a month to try

Create free account

Starter

≈$14 / month

250,000 rows a month

For regular exports to vendors, auditors or test systems

Pro

≈$33 / month

5,000,000 rows a month

For data teams and large extracts

  • ✓CSV and Excel files
  • ✓Names, emails, phones, SSNs, cards, IBANs, addresses
  • ✓Consistent pseudonyms across files
  • ✓Key file to restore originals
  • ✓Free-text scanning
  • ✓Files never leave your browser

Prices in USD are approximate. Checkout charges the exact amount in USD at Stripe’s exchange rate (a 2–4% conversion fee is included), or in euros if you prefer. No VAT or sales tax is added. Monthly, cancel any month. A row is one data row below the header; the same file is counted once, and restoring is free.

Questions

Can I process database exports?
Export the table to CSV and process it here. For many tables, process each with the same key file so the pseudonyms match.
Are amounts and other numbers changed?
Only if you choose to. Generalize puts numbers into ranges; by default columns that are not personal data are kept unchanged.