Bonnard FAQs

Question 1

What kind of data sources can Bonnard connect to?

Accepted Answer

Bonnard supports a wide range of data sources, including major data warehouses like Snowflake, Google BigQuery, Databricks, PostgreSQL, and Amazon Redshift. It also integrates with data tools like dbt, Dagster, and Prefect.

Question 2

What is Bonnard and its primary purpose?

Accepted Answer

Bonnard is an agent-native analytics platform with a command-line interface (CLI) that unifies semantic layer definitions. Its primary purpose is to provide consistent data and governed metrics across AI agents, applications, and dashboards.

Question 3

What are the core benefits of using Bonnard's semantic layer?

Accepted Answer

Bonnard's semantic layer ensures a single source of truth for your metric definitions. This eliminates data drift, provides consistent answers across all data consumers (AI agents, applications, internal tools, dashboards), and streamlines data governance.

Question 4

How does Bonnard support AI models and agents?

Accepted Answer

Bonnard generates agent context out of the box for AI models like Claude Code, Cursor, and Codex, helping them understand your semantic layer. It also offers an MCP (Model Context Protocol) server for governed agent queries, ensuring reliable and consistent answers.

Question 5

Can Bonnard be used to create dashboards?

Accepted Answer

Yes, Bonnard allows you to create rich markdown dashboards with various chart components (BigValue, LineChart, BarChart, etc.). These dashboards can be previewed locally and deployed to share governed insights.

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Key Features

Use Cases

Key Features

Use Cases