> For the complete documentation index, see [llms.txt](https://docs.kiln.tech/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.kiln.tech/docs/synthetic-data-generation.md).

# Synthetic Data Generation

Anyone can create thousands of synthetic data samples in just a few minutes using our interactive UI.

<figure><img src="/files/wKlx61fGu9bta0qP6a0l" alt=""><figcaption></figcaption></figure>

## Use Cases

Synthetic data is helpful for many reasons:

* **Evals:** Generate data for custom evals of your task performance
* **Fine-tuning:** Generate fine-tuning datasets
* **Built-in Quality Templates:** Use our built-in data-gen templates like 'Jailbreak' or 'Bias' to check your system for common issues (curated evals)
* **Addressing Bugs / Issues:** generate targeted data to reproduce a bug/issue, which can be used for training a fix, evaluating a fix, and backtesting
* **Prompting:** Generate examples to be used for few-shot or multi-shot prompting

## Get Started

There are 2 portions of synthetic data in Kiln:

* [**Synthetic Data Guide**](/docs/synthetic-data-generation/synthetic-data-guides.md) **(optional):** Kiln learns what great data looks like, to generate even better data for your task.
* [**Generating Synthetic Data**](/docs/synthetic-data-generation/generating-synthetic-data.md): build synthetic datasets for evals or fine-tuning