Introduction

Introduction

Cube is the business intelligence platform powered by the open-source semantic layer.

Cube uses AI agents to build data models and enable data consumers to perform analysis. Use AI to quickly build semantic layer and fully control the analytics context.

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Cube is a new generation of a business intelligence and embedded analytics platform built to be used by both humans and AI agents. It empowers different personas across your organization:

• Data Engineers can quickly curate data models with AI assistance, accelerating the development and maintenance of semantic layers
• Data Analysts can perform deep analysis with AI assistance, diving into complex data relationships and patterns
• Business Users benefit from workbooks and dashboards that Cube can automatically build and maintain

How is Cube different?

At the foundation of Cube's agentic analytics platform is an open-source semantic layer — the critical infrastructure that enables both AI agents and humans to work with trusted, consistent data.

Semantic SQL

Unlike other tools, Cube AI agents don't query the data warehouse directly. Instead, they query the semantic layer using Semantic SQL, creating a trusted proxy architecture.

Semantic layer architecture

Code-first

A code-first approach is essential for both traditional data engineering and agentic analytics. Managing data models, configurations, and policies as code enables the same proven practices that power modern software development.

Everything within Cube — from configurations to data models to access control policies — is managed through code.

Data Modeling

The data model provides the knowledge graph that AI agents use to understand your business. Cube's data model is code-first and dataset-centric, inspired by dimensional modeling. You work with two types of objects:

• Cubes represent business entities such as customers, line items, and orders
• Views sit on top of the data graph of cubes, creating facades that data consumers interact with

Access Control

Access control ensures that AI agents respect the same data security policies as human users. Cube's code-first approach enables data teams to define access control policies with Python or JavaScript.

Caching

Caching enables AI agents to deliver fast, interactive experiences without overwhelming your data infrastructure. Cube implements caching through pre-aggregations — rollup tables that accelerate query responses and reduce data warehouse costs.

APIs

APIs enable AI agents, applications, and tools to interact with the semantic layer through standard protocols: REST (JSON), GraphQL, and SQL.