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. 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.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.
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.
Start with the TPC-H walkthrough
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.
Explore the docs
Model your business
Design entities, relations, metrics and domains that
represent your data and business.
Ground AI on your data
Create a context layer for your data model, with skills
and instructions relevant for your business.
Connect BI and SQL
Connect Power BI, Tableau, Excel and any other user tool live
to your shared source of truth.
Connect AI agents
Build the semantic model from a coding agent, and query it in
natural language from Slack, Teams or other AI agents.