Stop building with fake data that breaks your tests. Start with realistic data that actually works.

Traditional mock data tools like Faker generate obviously synthetic values that don't reflect real-world complexity. LLMs like ChatGPT create realistic content but lack the structure and coherence your applications need.

MOSTLY AI's mock data generation bridges this gap. Our LLM-powered approach creates schema-compliant, multi-table datasets that mirror real-world structure and behavior—without ever touching production data or exposing personal information.

Generate realistic customer profiles with coherent addresses, purchase histories, and behavioral patterns. Create test datasets for financial transactions, healthcare records, or e-commerce flows that actually make sense together. All while maintaining referential integrity across tables and realistic distributions within columns.

Your mock data integrates seamlessly into CI/CD pipelines, supports development and QA environments, and gives you the confidence to build, test, and demo with data that behaves like the real thing.

Privacy-safe, production-like, and built for teams who need test data that doesn't break under pressure.