> ## 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 Auto-Explain

> What Auto-Explain is, how its root-cause analysis helps users, and 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>

Auto-Explain performs automated root-cause analysis on a cube. Starting from a variation between two cells, it drills down through the cube's hierarchies to find the members that most contribute to that variation, and reports them with their contribution percentages.

## How it helps

* Turns "why did this number change?" into an answer in a few clicks, without manual drill-down.
* Produces deterministic results — contribution percentages and contribution tables — that are always available, even without an LLM.
* Optionally generates a natural-language AI summary of the results when an LLM is configured.

## Learn more and set up

1. [How Auto-Explain works](../auto-explain/how-it-works) — the algorithm and a worked example
2. [Configure Auto-Explain](../auto-explain/configuration) — the constants and how to tune them
3. Set it up in the SDK you use: [Java](../auto-explain/setup-java) or [Python](../auto-explain/setup-python)