> 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/explore/sdv-bundles/ai-connectors.md).

# ❖ AI Connectors

Use the **AI Connectors bundle** to directly connect your database to SDV. This bundle offers a seamless integration with SDV synthesizers, with features that are specifically designed for generative AI.

**⭐️ Detect metadata based on the database schema.** Database schemas contain details about the column names and types of connections between tables. AI Connectors use this information to create [Metadata](/sdv/integration/metadata.md), which is a higher level specification needed for generative AI.

**⭐️ Import a data subsample that is AI-ready.** The data you input into a generative AI needs to be high quality. For example, it should have high coverage and it should not contain broken links. AI Connectors import a data subsample that is ready for AI.

**⭐️ Export synthetic data in the same format as the original.** Many users want to export synthetic data into a new database for downstream use. AI Connectors ensure that the exported database has the same format as the original database, allowing you to easily access the synthetic data in downstream applications.

{% hint style="info" icon="user" %}
Bundles are available to licensed users. Sign up now to get your license key. You can then complete your installation on-prem and begin using the features.

<p align="center"><a href="https://portal.datacebo.com/signup" class="button primary">Get Started</a><a href="https://datacebo.com/pricing/" class="button secondary">View Pricing</a></p>
{% endhint %}

## Included Features

This bundle includes AI Connectors for a variety of different databases.

<table data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-target data-type="content-ref"></th><th data-hidden data-card-cover data-type="image">Cover image</th></tr></thead><tbody><tr><td align="center">❖ <a href="/sdv/integration/db/integration/alloydb.md"><strong>AlloyDB</strong></a></td><td><a href="/sdv/integration/db/integration/alloydb.md">❖ AlloyDB</a></td><td><a href="https://1967107441-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FfNxEeZzl9uFiJ4Zf4BRZ%2Fuploads%2FkJ1bOR4AbOLLD1SkiFzg%2FAlloyDB.png?alt=media&amp;token=cf944e36-a8d7-473f-9938-633d50a770fd">AlloyDB.png</a></td></tr><tr><td align="center">❖<a href="/sdv/integration/db/integration/bigquery.md"> <strong>BigQuery</strong></a></td><td><a href="/sdv/integration/db/integration/bigquery.md">❖ BigQuery</a></td><td><a href="https://1967107441-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FfNxEeZzl9uFiJ4Zf4BRZ%2Fuploads%2FuYpWlTYYH1CYOr07wzfG%2FBigQuery.png?alt=media&amp;token=cd7b2e45-cd8b-4132-a06f-5518ce84f829">BigQuery.png</a></td></tr><tr><td align="center">❖ <a href="/sdv/integration/db/integration/mssql.md"><strong>MSSQL</strong></a></td><td><a href="/sdv/integration/db/integration/mssql.md">❖ MSSQL</a></td><td><a href="https://1967107441-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FfNxEeZzl9uFiJ4Zf4BRZ%2Fuploads%2FPHBms1a4bQgSdGQKCAoJ%2FMSSQL.png?alt=media&amp;token=a6f2021f-1cfa-4b09-9243-0173db44fc4a">MSSQL.png</a></td></tr><tr><td align="center">❖ <a href="/sdv/integration/db/integration/oracle.md"><strong>Oracle</strong></a></td><td><a href="/sdv/integration/db/integration/oracle.md">❖ Oracle</a></td><td><a href="https://1967107441-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FfNxEeZzl9uFiJ4Zf4BRZ%2Fuploads%2FZfj0JCHAUEh35s1qaTsk%2FOracle.png?alt=media&amp;token=a8ba5d36-54ef-476c-9557-86a6ecf676f8">Oracle.png</a></td></tr><tr><td align="center">❖ <a href="/sdv/integration/db/integration/postgresql.md"><strong>PostgreSQL</strong></a></td><td><a href="/sdv/integration/db/integration/postgresql.md">❖ PostgreSQL</a></td><td><a href="https://1967107441-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FfNxEeZzl9uFiJ4Zf4BRZ%2Fuploads%2FaoQYOyetcdahpAvL3aAS%2FPostgreSQL.png?alt=media&amp;token=4ad8e042-3ffd-4af7-98b4-584ac6191884">PostgreSQL.png</a></td></tr><tr><td align="center">❖ <a href="/sdv/integration/db/integration/spanner.md"><strong>Spanner</strong></a></td><td><a href="/sdv/integration/db/integration/spanner.md">❖ Spanner</a></td><td><a href="https://1967107441-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FfNxEeZzl9uFiJ4Zf4BRZ%2Fuploads%2FYlYJaZhTyVM24IriuOns%2FSpanner.png?alt=media&amp;token=6f0a8473-7699-42fa-9783-358ee372bedf">Spanner.png</a></td></tr></tbody></table>

## Installation

Use your SDV Enterprise credentials to install the AI Connectors bundle with the database that you'd like to use (see [the docs](/sdv/integration/overview.md#connect-to-a-database)).

```bash
% pip install sdv-installer --upgrade
% sdv-installer install --package bundle-ai-connectors --options db-bigquery db-mssql
```

```
Username: <email>
License Key: ********************************

Installing Bundles:
bundle-ai-connectors - Installed!

Success! All packages have been installed. You are ready to use SDV Enterprise.
```

{% hint style="info" %}
For more information about installing SDV Enterprise features and bundles, see our [**Enterprise Installation Guide**](https://docs.sdv.dev/sdv-enterprise/sdv-enterprise/installation).
{% endhint %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.sdv.dev/sdv/explore/sdv-bundles/ai-connectors.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
