nao - Natural Language Queries on Data Warehouses

Open-source analytics agent builder for context-engineered AI data exploration

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Updated Jul 2026 · Added Jun 2026

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What is Nao?

nao is an open-source analytics agent builder that enables teams to deploy AI-powered data exploration without coding. It works by organizing your data context - warehouse schemas, metrics, documentation, and rules - in a file system structure, then uses Claude to answer natural language questions about your data. Built for data teams, analysts, and business users who need instant analytics access without SQL knowledge.

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Key Features of Nao

File system-based context organization
Multi-database support (BigQuery, etc.)
Automatic context synchronization from dbt, Looker, Notion
Context reliability testing and monitoring
Natural language to SQL translation
Deployable chat UI
Multi-channel deployment (Slack, Teams, WhatsApp, Telegram, Claude, Cursor)
Self-hosting with your own LLM keys
Context engineering optimization
Unit testing for question-to-SQL accuracy

Who Should Use Nao?

Enable non-technical users to query data in plain English

Automatize analytics exploration with AI agents

Monitor agent reliability and context performance

Deploy analytics across team communication tools

Self-host analytics with data governance control

Reduce SQL query writing overhead for data teams

Nao: Pros & Cons

✓Pros

100% open source
Context engineering approach improves reliability
Supports multiple data sources and repositories
Flexible deployment options (cloud or self-hosted)
Integration with existing tools (dbt, Looker, Notion)
Context testing provides measurable reliability metrics
Multi-channel deployment capability

Frequently Asked Questions about Nao

Does nao support data warehouses other than BigQuery?

The documentation mentions BigQuery specifically, but nao is built to support multiple databases. Check the repository or documentation for the current list of supported warehouses before connecting your primary data source.

Can I deploy nao to Slack, Teams, and other chat platforms at the same time?

Yes. nao supports multi-channel deployment across Slack, Teams, WhatsApp, Telegram, and Claude, so you can run the same analytics agent in multiple team communication tools simultaneously.

How does nao test whether its context actually improves query accuracy?

Nao includes context reliability testing and unit testing for question-to-SQL accuracy, so you can measure whether your organized schemas, metrics, and documentation are actually helping the agent return correct results. This testing happens before you deploy to your team.

Can I run nao with my own LLM instead of relying on Anthropic's Claude?

Nao supports self-hosting with your own LLM keys, giving you control over which model processes queries and where your data context lives. This setup is intended for teams with data governance requirements.