The author, Head of Data at nao, evaluated 14 analytics agents to determine which tools can empower all team members to analyze data without needing advanced SQL skills. The goal was to establish reliable, user-friendly, and cost-effective solutions. After assessing various options, the author found that the market lacks a clear frontrunner, with many teams either building custom solutions or experimenting with existing tools. Key evaluation criteria included user experience, reliability, speed, cost, and the ease of setup for data teams. The author tested these tools using a real-world scenario involving user churn data, which highlighted the complexities of integrating data from multiple sources. Among the tools reviewed, Databricks Genie stood out for its monitoring and evaluation framework, while Snowflake Cortex struggled with usability for broader teams. Tools like Looker and Metabase faced limitations with self-service capabilities and user feedback suggested unreliability in their AI features. Other notable mentions included Omni, praised for its integration with dbt semantics but criticized for its high cost. Lightdash and Hex offered ease of setup but had limitations in configuration and speed. Claude and Dust provided flexibility, yet required significant setup effort. The article emphasizes the ongoing challenge of finding a comprehensive solution that balances ease of use with reliable performance and cost efficiency.