# Testset Generation

Curating a high quality test dataset is crucial for evaluating the performance of your AI application.

## Characteristics of an Ideal Test Dataset

- Contains high quality data samples
- Covers wide variety of scenarios as observed in real world.
- Contains enough number of samples to derive statistically significant conclusions.
- Continually updated to prevent data drift

Curating such a dataset manually can be time-consuming and expensive. Ragas provides a set of tools to generate synthetic test datasets for evaluating your AI applications.

- [**RAG** for evaluating retrieval augmented generation pipelines](https://docs.ragas.io/en/stable/concepts/test_data_generation/rag/index.md)
- [**Agents or Tool use** for evaluating agent workflows](https://docs.ragas.io/en/stable/concepts/test_data_generation/agents/index.md)