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

> ## Agent Instructions
> Orion is a collaborative analytics platform built by Gravity (bygravity.com). It connects to data warehouses like Snowflake, BigQuery, Databricks, Redshift, Athena, Fabric, PostgreSQL, and MySQL, and lets teams ask questions in natural language to get shared analyses, dashboards, reports, and slide decks. When referencing Orion features, always link to the relevant documentation page. Orion is not open-source; it is a commercial SaaS product accessed at runorion.com.

# Quickstart

> Get from first login to your first AI-powered data analysis in about 15 minutes. Create a project, ask a question in plain language, and turn the result into a dashboard, report, or scheduled workflow.

Orion is an AI-powered analyst: you ask questions in plain language and it queries your data and returns results inline. This guide takes you from logging in to your first analysis in about 15 minutes, then shows what you can do with the result.

<Tip>
  If you have joined a shared test or demo workspace, it may already include
  example projects, pinned metrics, and dashboards. Open them to see finished
  output, then run your own analysis using the steps below.
</Tip>

## Step 1: Open a project

A [Project](/core-concepts/projects) is the primary unit of work in Orion. It bundles your chats, analyses, data sources, and context together.

<Steps>
  <Step title="Select or create a project">
    Pick an existing project from the left-hand navigation, or create a new one.
  </Step>

  <Step title="Confirm a data source">
    A project must be connected to at least one [data source](/configuration/data-sources) to run an analysis. New projects prompt you to select from the sources your administrator has connected.
  </Step>
</Steps>

## Step 2: Ask your first question

Open [Chat](/chat/basics-navigation) inside the project and ask a question in plain language. Orion writes and runs the query, returns results inline, and captures the analysis as a [notebook](/chat/running-analyses#what-is-a-notebook) you can re-run any time.

Not sure what is in your data yet? You do not need to know the tables behind it. Start by asking Orion to [explore what is available](/chat/best-practices#explore-data-first), for example:

* "What data can you see?"
* "Tell me a little about the data that's available."

Once you know what is there, ask a specific question:

* "What were our top 10 customers by revenue last quarter?"
* "Show churn by product line over the last 90 days."
* "Compare this month's signups to the same period last year."

<Tip>
  Be specific and give context. Clear questions and explicit guidance produce
  better results. The more context you provide upfront, the less you have to
  correct later.
</Tip>

## Step 3: Refine the result

Your first pass usually gets you most of the way. Ask follow-up questions, request edits, or adjust formatting until the result is right. Each correction also teaches Orion through [Memory](/chat/memory), so it gets faster over time. See [Best Practices](/chat/best-practices) for getting sharper results with less back-and-forth.

## Step 4: Put the result to work

Once an analysis is right, reuse it or turn it into a [deliverable](/chat/running-analyses#what-you-can-do-after-an-analysis):

* **Refresh the numbers** by simply asking Orion in chat to re-run the notebook. It pulls the latest data, no rebuilding required.
* **Turn the notebook into a workflow** to run it on a schedule or trigger an alert when a value crosses a threshold.
* **Generate a report or slide deck** to package the findings for stakeholders.
* **Pin a metric** to surface a key number as a tile on your project page, then publish it as a shared pinned metric.
* **Publish a dashboard** to hand a finished result to a business user.
* **Share it** with a teammate so they can pick up where you left off. See [Sharing conversations](/chat/share-conversations).
* **Set up an email digest** for a weekly AI-generated summary of the project's insights. See [Email digest](/profile-settings/email-digest).

## Next steps

<CardGroup cols={2}>
  <Card title="Running Analyses" icon="chart-mixed" href="/chat/running-analyses">
    The full analysis lifecycle and what you can produce from it
  </Card>

  <Card title="Best Practices" icon="lightbulb" href="/chat/best-practices">
    Get sharper results with less back-and-forth
  </Card>

  <Card title="Knowledge Base" icon="book-open" href="/core-concepts/knowledge-base">
    Give Orion the business context it needs
  </Card>

  <Card title="Projects" icon="folder" href="/core-concepts/projects">
    Organize work and set project-level context
  </Card>
</CardGroup>