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

# Introduction

Honeydew is the Semantic Layer for AI and BI. You define your business
entities, metrics, relationships and access controls once, and use them everywhere.
Honeydew serves them through SQL, XMLA, GraphQL and MCP, to BI tools
like Power BI, Tableau and Excel, to SQL clients, to coding agents, and to the
[Honeydew AI Analyst](/integration/context-layer/deep-analysis).

Metrics are *context-aware*. A metric is defined once at its entity's
granularity and recomputes correctly across any slice, filter, group or
join a user needs. `revenue` means the same thing whether
it's grouped by region in a Tableau dashboard or returned by an AI
agent investigating a quarterly drop, and stays consistent as the
model evolves.

<Card title="Start with the TPC-H walkthrough" href="/tpch-example" icon="play">
  Build a working Honeydew on the TPC-H sample data: semantic model,
  domain, context layer, agent, a BI tool live on the domain, and
  Deep Analysis.
</Card>

## Explore the docs

<CardGroup cols={2}>
  <Card title="Model your business" href="/architecture">
    Design entities, relations, metrics and domains that
    represent your data and business.
  </Card>

  <Card title="Ground AI on your data" href="/integration/context-layer/overview">
    Create a context layer for your data model, with skills
    and instructions relevant for your business.
  </Card>

  <Card title="Connect BI and SQL" href="/integration/bi-tools/supported-tools">
    Connect Power BI, Tableau, Excel and any other user tool live
    to your shared source of truth.
  </Card>

  <Card title="Connect AI agents" href="/integration/context-layer/building-with-ai">
    Build the semantic model from a coding agent, and query it in
    natural language from Slack, Teams or other AI agents.
  </Card>
</CardGroup>