Synthetic test data, without touching production

Seedfast generates synthetic test data from your live database schema, so an empty environment gets a full, coherent dataset with no production records in it. Point it at a schema, run one command, and every table comes back filled — foreign keys resolved, constraints and check rules satisfied.

Cloning or anonymizing production data is harder and more expensive than it looks. The tools that handle relational integrity properly are mostly enterprise-grade and contact-sales: slow to procure, slow to integrate, and a real cost line in the budget. And even with the right tooling in place, real customer data still leaves the production boundary; you've reduced the risk, not removed it. Seedfast skips the whole loop. Nothing real ever leaves production, so there's nothing to anonymize and no vendor pipeline to maintain.

Faker generates values for individual fields. It doesn't understand how your tables connect. You're left writing the relational logic yourself: making sure references point to rows that actually exist, totals add up across related tables, values respect the constraints you've defined, and everything inserts in the right order. Every schema change means rewriting those scripts. Seedfast reads your schema and produces data that's coherent across tables, relationships, and constraints out of the box.

No. Seedfast works from your schema alone: DDL files, migrations, or a connection to a non-production database is enough. Production data never enters the workflow.

Schemas are generally treated as non-sensitive metadata under the major regulatory frameworks (GDPR, HIPAA, PCI-DSS, SOC 2), which target the data inside the schema, not the structure itself. Seedfast is built around your schema, not your data, which is why it's a clean fit for regulated industries. If your internal security policy classifies schemas as proprietary, get in touch and we'll walk through the specifics.

PostgreSQL, including Supabase, Neon and Amazon RDS. We went PostgreSQL-first because it has the richest constraint and relationship system, which is exactly where realistic seeding gets hardest. Support for other SQL engines, including MySQL, Oracle and SQLite, is in development.

Yes. Foreign keys, composite keys, multi-level dependencies, check constraints, unique constraints, enums, JSON columns, and triggers are all handled. Seedfast works out the right insertion order, generates values that satisfy the constraints, and writes the data in a sequence your database will accept.

Realistic enough to pass a code review and run your application against. Names look like names, emails look like emails, monetary values fall within sensible ranges, and relationships make sense, so an order belongs to a customer who exists, line items sum correctly, timestamps line up. Seedfast also infers the shape your data should take in production: long-tailed totals, skewed enums, business-hour clusters, and table sizes proportioned like the real database. Distributions feel like the live system, not a uniform random fill. When the defaults aren't quite right, you can configure row counts per table and shape how specific columns get filled.

Every plan includes a monthly pool of credits. Each seed draws from it based on how much data it generates, with no table or seed limits. If you run out before the month is up, you can top up or move to a larger plan.

A seeding run has two phases: scoping, where Seedfast reads your schema and works out what to generate, and the generation itself. A full session on a mid-size schema of around 30 tables, including the back and forth while you get it right, costs about 60 cents in credits, and the number of rows you generate barely changes that. That puts the free plan at roughly 8 runs a month, Basic at around 50, and Premium at around 300.