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

# Getting Started

Get answers from your data in under 10 minutes.

Not using Dot yet? [Sign up for free.](https://app.getdot.ai/register)

***

## 1. Connect Your Data

Go to **Settings → Connections** and add your data warehouse, semantic layer, or BI tool.

No code required—just permissions.

<figure><img src="https://3709841693-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FCeRlmJf2y704TpjpubE1%2Fuploads%2Fgit-blob-c03f9b452342f5b9a41f6b795c7ac66e3ab4100d%2Fconnections-page.png?alt=media" alt="Connect databases like Snowflake, BigQuery, Postgres, or semantic layers like dbt, Looker, and Power BI"><figcaption></figcaption></figure>

[See all integrations →](/integrations/databases.md)

***

## 2. Describe What You Need

Open the **Context Agent** and tell it what you're trying to accomplish. It will interview you, explore your data, and set things up.

<figure><img src="https://3709841693-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FCeRlmJf2y704TpjpubE1%2Fuploads%2Fgit-blob-d9f8b39d9b02ee6e4d6576025753d0cb81b79fce%2Fcontext-agent-interview.png?alt=media" alt="Context Agent interviewing a user about their product analytics use case"><figcaption></figcaption></figure>

You don't need to configure everything upfront—start with one use case and expand from there.

[Learn more about the Context Agent →](/train-dot/context-agent.md)

***

## 3. Start Asking Questions

Ask in plain English. Dot queries your data, visualizes results, and explains what it found.

You can ask questions directly in Dot, or connect Slack or Microsoft Teams so your whole team can get answers where they already work.

<figure><img src="https://3709841693-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FCeRlmJf2y704TpjpubE1%2Fuploads%2Fgit-blob-82f4819e6905ccf4473e1387278df38595f16dba%2Fslack-chat.png?alt=media" alt="Team members asking Dot questions in Slack and getting answers with charts"><figcaption></figcaption></figure>

[Set up Slack & Teams →](/integrations/slack-and-teams.md)

***

## What's Next

**Fine-tune how Dot understands my data**\
[Model →](/train-dot/model.md)

**Control who can access what**\
[Permissions →](/train-dot/permissions.md)

**Schedule recurring reports**\
[Scheduling →](/using-dot/scheduling.md)


---

# 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.getdot.ai/getting-started.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.
