Skip to content
Concepts

Synthetic Data

Artificially generated data used to train AI models when real data is scarce, expensive, or privacy-sensitive. AI can generate realistic text, images, and tabular data that supplements or replaces real-world datasets.

Why it matters

Synthetic data helps teams train AI when real examples are rare, expensive, or too sensitive to use, such as medical records or fraud cases. It can fill gaps, balance underrepresented scenarios, and sidestep privacy risks. This matters because the quality and fairness of a model depend heavily on its training data, and synthetic data offers a controllable way to improve coverage without exposing real people's information.

In practice

A bank wants to train a fraud detector but has very few real fraud examples and can't share customer data freely. Engineers generate realistic but fake transaction records that mimic fraud patterns, then train on them. A caution worth knowing: if the synthetic data misses real-world messiness, the model may look great in testing yet stumble on genuine cases, so it's usually blended with real data.

Related terms

Put Synthetic Data into practice

Access 800+ AI models and 70+ tools through Vincony — start free with 100 credits.