> For the complete documentation index, see [llms.txt](https://docs.sdv.dev/sdv/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sdv.dev/sdv/welcome-to-the-sdv.md).
# Welcome to the SDV!
The **Synthetic Data Vault** (SDV) is a Python library designed to be your one-stop shop for creating tabular synthetic data.
## Key Features
:brain: **Train your own generative AI model.** Choose from a variety of AI algorithms designed for tabular data — single table, sequential, or multi-table (relational) data. Train your own synthesizer using your real data, and create any amount of synthetic data on-demand. SDV is designed to work on-prem, with standard CPUs.
:bar\_chart: **Evaluate & visualize synthetic data.** Measure the statistical quality of your synthetic data and diagnose problems. For even more insight, create visualizations that compare your synthetic data with your real data.
:gear: **Customize your synthesizer.** The SDV platform offers powerful features for creating higher quality synthetic data. You can add constraints, adjust the data preprocessing, and selecting anonymization options for any SDV synthesizer.
## Install SDV Community
## Take synthetic data to the next level with SDV Enterprise
**SDV Enterprise** is available to licensed users. With SDV Enterprise, you'll have access to everything in SDV Community *plus the ability to ...*
:white\_check\_mark: Create synthetic data for large numbers of complex, interconnected data tables using scalable synthesizers
:white\_check\_mark: Improve the quality of your synthetic data with more advanced data preprocessing, deeper data understanding, and enhanced AI algorithms
:white\_check\_mark: Easily integrate data sources and deploy synthetic data applications enterprise-wide
To learn more, [**visit our website**](https://datacebo.com/pricing/).
{% hint style="info" icon="user" %}
SDV Enterprise is available to licensed users. Sign up now to get your license key. You can then complete your SDV Enterprise installation on-prem and begin using the features.
{% endhint %}
## Owned & Maintained by DataCebo
The SDV library is a part of the greater [Synthetic Data Vault Project](https://sdv.dev/), first created at MIT's Data to AI Lab in 2016. After 4 years of research and traction with enterprise, we created DataCebo in 2020 with the goal of growing the project.
Today, [DataCebo](https://datacebo.com/) is the proud developer of the SDV, the largest ecosystem for synthetic data generation & evaluation.
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