Pros
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Free
Usage-based
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Bonnard uses a governed semantic layer where metrics are pre-defined in YAML. AI agents query these governed definitions rather than raw database tables, ensuring accurate aggregations and preventing hallucinated results.
Yes, Bonnard offers an open-source Apache 2.0 licensed version that can be self-hosted via Docker Compose. There is also a managed cloud option for teams that prefer not to manage infrastructure.
Bonnard connects to standard data warehouses and automatically detects DBT models. It creates views and cubes from raw tables with built-in multi-tenant isolation.
Bonnard includes an MCP server that exposes your governed metrics to AI agents. Agents can query defined metrics through the Model Context Protocol, ensuring they always use accurate, governed data definitions.
Bonnard enforces row-level security per tenant with token-based authentication mapping. Every query automatically respects tenant boundaries, and all access is logged for compliance auditing.
Source: bonnard.dev