Synthetic data that doesn't break privacy rules. MostlyAI generates mock datasets from your production data while keeping everything locked down in your environment. TabularARGN creates high-fidelity synthetic records that look real but aren't. Training happens 100x faster than traditional methods.
Data scientists stuck with sanitized development datasets finally get something useful. You can pull insights from live enterprise systems without compliance teams breathing down your neck. MostlyAI turns natural language questions into Python code for analysis. Swiss Post got 89% more access to customer data using this approach.
Feed your production database into MostlyAI. It spits out synthetic records that mirror the statistical patterns. Need to test edge cases? Generate a million samples with whatever weird scenarios you want.
The cloud version handles enterprise workloads. There's also an open source SDK under Apache v2 license — keeps everything local in Python. Works with Databricks. Kubernetes too. AWS environments as well.
Production data access remains limited even with synthetic alternatives. You're still working with approximations of reality. Some data teams report access increases from 11% to 100%. Results vary depending on your organization's privacy constraints.
Free accounts get you started. Enterprise pricing isn't published, which usually means it's expensive. Data engineers dealing with GDPR compliance will find this more practical than endless anonymization workflows.
