Tonic.ai generates realistic fake data for testing so your production database never goes near your dev environment

If you work with production data in development and testing environments you already know this is a problem. Real customer records, real PII, real financial data sitting in environments with looser access controls and more people touching them than your production systems. Most teams know this is a risk and deal with it imperfectly because the alternative, building and maintaining realistic fake datasets manually, is genuinely painful.

Tonic Structural solves this by generating synthetic data that is de-identified but functionally realistic. The automatic PII detection scans your databases and identifies sensitive fields, names, social security numbers, credit card numbers, addresses, without you having to map them manually. It then replaces those fields with realistic fake equivalents that maintain the same format and data type so your application code does not know the difference.

Referential integrity is the detail that determines whether synthetic data is actually usable for complex testing. If you replace a customer ID in one table, every related record across all tables needs to reference the new ID consistently. Tonic handles this automatically, which is what makes the synthetic data functional for real application testing rather than just passing a data format check.

Database Subsetting creates smaller portable versions of massive production databases while keeping all related records intact. For development environments where you do not need the full production volume but do need representative data with all relationships preserved, that is a practical tool.

Coverage includes PostgreSQL, MySQL, Snowflake, BigQuery and Amazon S3. The Privacy Hub gives you a centralized view of data protection progress and compliance status against GDPR and HIPAA requirements.