Cube grounds every AI agent on a single governed model — so the answer is the same whether it comes from Analytics Chat, Claude, ChatGPT, Slack, or an agent you build yourself.
Just like these companies:
Analytics Chat
Ask in plain English. The agent writes and runs the queries against your semantic model — no SQL required.
Refine iteratively; context, filters, and prior queries carry forward across the thread.
Charts, tables, and the reasoning behind them — every number governed and scoped to each user.
Workbooks
Reports, charts, and dashboards from a request — while you keep control of every field, filter, and label.
Point-and-click, raw SQL, or Semantic SQL on top of governed metrics — all in one place.
Every chart is backed by a reusable, governed report.
Dashboards
Break a metric down, extend the range, or explain a definition — read-only, on the same governed model.
Chart, KPI, filter, time-grain, text, and AI Summary widgets.
Scheduled refreshes, PNG and PDF snapshots, and embed-anywhere.
Data Modeling
Generate a model from your warehouse tables, convert existing LookML, or extend definitions in SQL-first YAML.
Every agent reasons over governed definitions instead of raw tables — which is what makes the answers trustworthy.
Row-level security flows from the model to every answer, on any warehouse.
Integrations
Claude, ChatGPT, Cursor, or one you build — each queries your governed model as a tool.
Drop the Slack Agent into a thread; ask and follow up where your team already works.
Can't see a metric in Cube? You won't see it in Slack either.
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
See how Cube can help you get the most of your data