Cube grounds your AI on a single governed model — so the same question gets the same answer across chat, workbooks, dashboards, Claude, ChatGPT, and Slack.
Just like these companies:
Architecture, Not a Feature
Most BI tools are dashboard-first or notebook-first, with AI bolted on later. Cube was built around the semantic layer from day one — which is what makes the AI useful, not just present.
AI queries your governed model directly — no schema-guessing, no hallucinated metrics, no fifteen versions of active user.
Asked in chat, a workbook, a dashboard, or over MCP — every answer ties back to the same governed definitions.
Row-level security and access controls hold from the model down to every answer your team sees.
Open-Source Foundation
Cube Core is Apache-licensed and battle-tested across years of production use. The agentic platform stands on a foundation you can read, run, and trust — not a closed box.
Agentic Surfaces
Natural-language analytics, grounded by default — no SQL required.
Speed and Governance
Pre-aggregations and caching keep queries fast on big tables at high concurrency.
A SQL-first semantic layer that's extensible at query time, so analysts don't wait for the data team.
Governance flows from the model through every surface — no fifteen versions of active user.
Goes Where Your Team Works
Cube as the source of truth for any AI agent: Claude, ChatGPT, Cursor, or your own.
Natural-language analytics in your team's channels, governed by default.
The same architectural foundation, meeting your team where it already works.
The future of reporting isn't a chart, it's an insight. Large language models are becoming a commodity — the LLM is the engine, but the semantic layer is the map. A well-modeled ontology is the difference between 'I don't understand that question' and a correct, contextualized answer with a chart and a clear explanation. Cube gives us the foundation to make that real for every customer.Dan MeshkovStaff Software Engineer, BrexRead the Story
Cube becomes our single source of truth for metric definitions and powers everything from customer-facing dashboards to AI-driven quarterly business reviews. CSMs gain back dozens of hours each quarter, enabled by Cube’s semantic layer and agentic analytics.
Anthony Cronander
Senior Analytics Engineer, Drata
We integrated Cube Cloud smoothly with ClickHouse, leveraging both for fast query execution while maintaining the abstraction needed for different teams to access data without diving into database-specific complexities.
Rocio Delgado
Senior Engineering Manager at Webflow
Without Cube, our data analysts might have to write 20 different queries for a single core business metric. With Cube, that metric is defined once in the data model, and every downstream tool uses that definition along with the associated calculation logic.
Dr. Jun Huang
Global Head of Data Science at Alcon
One governed model. The same answer everywhere.
