Synthetic data guides
Choose a workflow, understand the tradeoffs and learn what to check before putting generated data to work.
Prefer to inspect the output? Download a worked example or compare generation approaches.
What is synthetic data?
Learn what synthetic data is, when to generate it from a prompt or existing data, and how to evaluate realism, utility and privacy in Ground.
Read guide →How to generate synthetic test data
Build realistic test datasets for pipelines and applications with reproducible seeds, missing values, rare cases and related tables in Ground.
Read guide →Using synthetic data for machine learning
Extend training datasets, rebalance rare labels and evaluate synthetic data against real holdout data with Ground's quality and privacy report.
Read guide →How to evaluate synthetic data quality
Evaluate synthetic datasets with column fidelity, relationships, detection AUC, TSTR and privacy checks. Learn what Ground's report measures and what it cannot prove.
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