Holistics - Business Intelligence Tool

Holistics

Holistics

Founded by Vincent Woon in 2015

Build self-service BI dashboards where AI answers match your governed metrics

Cost

Free Trial

Rating

People love it

Time to value

Moderate Setup (1-3 hours)

You can use Holistics to build a governed analytics layer where data teams define metrics once in code, and business users can explore data through drag-and-drop or ask questions in plain language. It connects a programmable semantic layer with an AI query engine, so answers from AI match what's shown in dashboards. Teams can version-control their models, metrics, and dashboards in Git, embed analytics in their own products, and connect to warehouses like Snowflake, BigQuery, and Databricks.

What Holistics does

Define reusable metrics and dimensions in code using the AML semantic layerQuery metrics by composing them on top of each other using AQL without writing raw SQLVersion-control dashboards and models in Git with full change history and rollbackAsk questions in plain language and get answers traced back to governed metric definitionsEmbed dashboards and AI query interfaces inside external products with row-level securitySchedule and deliver dashboard reports via email or Slack on a recurring basisDrill into any chart number to see the underlying data rows behind itConnect external AI tools like Claude or Cursor to your semantic layer via MCPDefine metrics once in a central semantic layer and reuse them across dashboards, AI answers, and embedded analyticsComposable query language (AQL) lets you build new metrics on top of existing ones without copy-pasting SQLAnalytics-as-code workflow with Git version control, pull requests, and rollback for all models and dashboardsAI answers questions in plain language by reading your governed metric definitions, not raw tablesAI asks clarifying questions when a request is ambiguous before generating an answerEmbed white-labeled dashboards and AI question-answering inside your own productBusiness users can drill down, slice by dimension, and view underlying row-level data without SQLConnect to Claude, ChatGPT, or Cursor via MCP so external AI tools read the same metric definitions

Tutorials & Demos

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