Wren AI is a generative business intelligence platform that converts natural language questions into SQL queries, charts, and insights from connected databases. It features a semantic layer for unified data modeling and supports various deployment options including open source, cloud, and on-premises. The tool integrates with data sources like BigQuery, PostgreSQL, MySQL, and Snowflake, and uses LLMs for processing.

Key functionalities include real-time conversational analytics for instant answers, explainable SQL for transparency, and a feedback loop that improves accuracy with user corrections. Security measures encompass row-level and column-level controls, role-based access, and audit logs. General pricing involves credit-based tiers from starter to enterprise, which provide scalable access compared to competitors.

Users value the reduction in SQL writing and faster insights, but may encounter variability based on LLM choice. Competitors such as Vanna focus on text-to-SQL, while Tableau emphasizes visualizations. Wren AI stands out with its embedded API and knowledge base.

The dashboard allows custom real-time views, and integrations with dbt and Trino enhance query efficiency. Potential surprises include AI-generated summaries that uncover unexpected patterns in data.

To implement Wren AI effectively, connect your primary data source first, define key metrics in the semantic layer, and start with simple queries before advancing to complex analyses.