Bonnard FAQs

Question 1

What is Bonnard?

Accepted Answer

Bonnard is an agent-native semantic layer CLI that deploys a governed analytics API for AI agents, BI tools, and data teams. It allows you to define metrics once and query them consistently from anywhere across your data stack.

Question 2

How does Bonnard support AI agents and AI coding?

Accepted Answer

Bonnard is built agent-native with Model Context Protocol (MCP) as a core feature. It automatically generates context files for AI coding agents like Claude Code, Cursor, and Codex, enabling them to understand, query, and interact with your semantic layer directly.

Question 3

Which data warehouses and tools does Bonnard integrate with?

Accepted Answer

Bonnard offers native integrations with Snowflake, Google BigQuery, Databricks, and PostgreSQL. It also detects and integrates with other data tools like dbt, Dagster, Prefect, Airflow, Looker, Cube, and more.

Question 4

What does 'define metrics once, query from anywhere' mean?

Accepted Answer

This core principle means you define your key business metrics and dimensions in Bonnard's YAML files. Once defined, these standardized metric definitions can be consistently accessed and queried by AI agents, BI dashboards, and data teams through a single, governed analytics API, ensuring data consistency across all consumers.

Question 5

Is Bonnard also beneficial for traditional BI tools and data teams?

Accepted Answer

Absolutely. While agent-native, Bonnard provides a governed analytics API that serves both cutting-edge AI agents and traditional BI tools, as well as human data analysts. It ensures that all stakeholders work with a single source of truth for metric definitions.

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Key Features

Use Cases