> ## Documentation Index
> Fetch the complete documentation index at: https://docs.activeviam.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Set up an LLM

> What a Large Language Model provides in Atoti Intelligence, why it is required, and the list of supported providers with links to the Atoti Java SDK and Atoti Python SDK setup pages.

<Info>
  ### Atoti Intelligence Essentials

  This is part of the Atoti Intelligence Essentials offer.
</Info>

A Large Language Model (LLM) is the AI model that powers Atoti Intelligence's natural-language features. Atoti Intelligence does not include a built-in model: you connect your own LLM provider.

## Why configure an LLM?

Configuring an LLM enables the following capabilities:

* Natural-language queries and responses
* AI-assisted visualization creation with Visualize This
* The optional AI summary of Auto-Explain root-cause analysis results

<Note>
  Auto-Explain's root-cause analysis works without an LLM. An LLM is only required to generate the optional AI summary of Auto-Explain results, and to use Visualize This.
</Note>

Atoti Intelligence connects to LLM providers through Spring AI, which supports multiple providers through a consistent configuration interface. See the [Spring AI documentation](https://docs.spring.io/spring-ai/reference/api/chat/comparison.html) for more information.

## Supported providers

Choose your provider below, then follow the page for the SDK you use:

* **Amazon Bedrock** — [Java](../llm/amazon-bedrock-java) / [Python](../llm/amazon-bedrock-python)
* **OpenAI** — [Java](../llm/openai-java) / [Python](../llm/openai-python)

<Note>
  Many LLMs support the OpenAI API format. A model from another provider may be compatible with the OpenAI configuration.
</Note>

## Next steps

After setting up an LLM, configure the AI tools:

* [Set up Auto-Explain](./set-up-auto-explain)
* [Set up Visualize This](./set-up-visualize-this)