testdatatools
AI & ML datasets

How should you evaluate synthetic data for AI and ML?

Match the evaluation target first: tabular distributions, domain text, documents or agent evaluation sets. NVIDIA now documents NeMo workflows in the area previously associated with Gretel. Former Gretel-branded service availability is not established here.

What changes the decision?

Statistical similarity, task utility and privacy are separate properties. A dataset can resemble a source and still fail downstream evaluation. Seed datasets steer generation; they do not establish a random-seed replay contract.

What should your proof of concept show?

Keep a real holdout outside training. Compare task performance, rare groups and constraints, then check disclosure or memorization risk. Ask for a versioned evaluation report rather than a single synthetic-data quality score.

These are editorial decision criteria, not measured product rankings. Follow the profiles below for product-specific source evidence.

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Product status changed

Gretel / NVIDIA

AI & ML datasets

Gretel was acquired by NVIDIA in 2025; NVIDIA now positions synthetic-data generation for agentic AI through NeMo. The availability of Gretel's former standalone platform is unconfirmed.