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getwren

by Community

Open-source GenBI for humans and AI agents. Wren AI turns plain-English questions into governed text-to-SQL, charts, and dashboards across 20+ data sources.

getwren screenshot

Agents

getwren

Added 10 July 2026

Overview

getwren is an open-source generative business intelligence tool that converts plain-English questions into SQL queries, charts, and dashboards. It supports over 20 data sources and includes governance features for both human users and AI agents.

Best for

Best for
Teams needing a governed, open-source way to let non-technical users and AI agents query databases via natural language.

Use cases

  • Ask natural language questions to generate SQL queries and visualizations
  • Build governed dashboards from multiple data sources without writing code
  • Enable AI agents to query databases through a text-to-SQL interface

Notes

getwren is an open-source generative business intelligence tool that converts plain-English questions into SQL queries, charts, and dashboards. It supports over 20 data sources and includes governance features for both human users and AI agents.

Use cases

  • Ask natural language questions to generate SQL queries and visualizations
  • Build governed dashboards from multiple data sources without writing code
  • Enable AI agents to query databases through a text-to-SQL interface

Pros

  • Open-source with community support, reducing vendor lock-in
  • Supports a wide range of data sources (20+) for flexible integration
  • Built-in governance for controlled access and query auditing

Cons

  • Requires setup and maintenance of the open-source infrastructure
  • May struggle with complex or ambiguous natural language queries
  • Limited to SQL-based data sources, not all data types

Indexed from awesome-ai-agents and enriched against its public facts.

Pros

  • Open-source with community support, reducing vendor lock-in
  • Supports a wide range of data sources (20+) for flexible integration
  • Built-in governance for controlled access and query auditing

Cons

  • Requires setup and maintenance of the open-source infrastructure
  • May struggle with complex or ambiguous natural language queries
  • Limited to SQL-based data sources, not all data types

Pairs with

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