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Honeydew provides tools for integrating AI into your data workflows. You can use AI coding agents to build and maintain your semantic model, query data with natural language, and embed AI-powered analytics into your applications.

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Use Cases

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Build a Semantic Model with AI

Use an AI coding agent to create and manage your semantic model through natural conversation — all without leaving your IDE. For example:
  • Bootstrap a new semantic model in minutes by importing warehouse tables and defining entities, relationships, and metrics
  • Export semantics from an existing semantic model, query, or data source
  • Quickly add and validate new metrics and attributes
  • Ask data questions and iteratively add and refine missing semantics
For setup instructions, see the MCP Server page.

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Query Data with Natural Language

Ask business questions in plain language and get data results or SQL queries. AI coding agents connected to Honeydew translate your questions into semantic queries, ensuring consistent and accurate results based on your governed metrics and entities. For example:
  • “What is the total revenue by region for the last quarter?”
  • “How many orders were placed last month?”
  • “Show me the top 10 customers by lifetime value”

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Embed AI Analytics in Applications

Build AI-powered data applications using the Honeydew AI API. The API supports natural language questions, multi-step deep analysis, and follow-up conversations — all grounded in your semantic model. You can integrate Honeydew AI into:
  • Custom chatbots and assistants
  • Internal data portals
  • Slack and Teams workflows (Slack App, Teams App)
  • Streamlit dashboards (Streamlit)

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Deep Analysis

Use the deep analysis capability for multi-step analytical workflows. The AI agent breaks down complex questions, runs multiple queries, and synthesizes the results into a coherent answer. For example:
  • “Why did revenue drop last quarter? Break down by region and product category.”
  • “Compare customer retention rates across acquisition channels over the past year.”
  • “Which product lines are underperforming relative to their growth targets, and why?”
  • “There was a spike in returns last week. Identify the root cause and affected segments.”
This is available through:
  • The AI API ask_deep_analysis_question endpoint
  • The MCP Server ask_deep_analysis_question tool combined with AI coding agent plugins and skills

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Getting Started

To start building with AI:
  1. Connect an AI coding agent — Set up the MCP Server in your preferred client (Claude Code, Cursor, VS Code, and more)
  2. Install plugins — Add the Honeydew plugins for guided semantic modeling and data analysis workflows
  3. Explore your data — Ask questions, build your model, and query data through natural conversation