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nao

nao

AI data IDE for 10x faster data work

Website getnao.io
Overview

What it is

Nao is an AI powered data IDE for analysts, engineers, and scientists to write SQL, Python, or dbt workflows, preview changes, catch issues early, and deploy confidently. It connects directly to your warehouse and understands your schema so you can build faster, fix fewer bugs, and maintain trust in your data. Build data pipelines, launch quality checks, run analytics, and collaborate across teams without context switching. Think of it as your AI teammate built specifically for modern data work.

Intent

I need it when

Enable non-technical business users to ask natural language questions about company data without SQL knowledge

nao deploys a chat UI where users ask questions in plain English, and the AI agent translates them to SQL queries against the data warehouse. This democratizes data access across the organization.

Maintain full data security and control by keeping analytics infrastructure within company infrastructure

nao offers self-hosted deployment where users bring their own LLM keys and everything runs in their infrastructure. This ensures data never leaves the organization while maintaining full control over the agent.

Build reliable AI agents that accurately answer data questions with minimal hallucination

nao uses context engineering to structure agent knowledge like a file system, pulling from databases, dbt repos, Looker models, and documentation. Users can test and measure context reliability with unit tests before deployment.

Synchronize and maintain accurate agent context as data models and documentation evolve

nao's sync feature automatically pulls context from databases, dbt repositories, and external sources like Notion, keeping the agent's knowledge current without manual updates.

Integrate analytics agents into existing communication workflows without building custom integrations

nao provides MCP support and integrations with Slack, Teams, WhatsApp, Telegram, Claude, and Cursor, allowing users to ask data questions from their preferred tools.

Drop

Not a fit when

  • User needs a fully managed analytics solution without technical setup or context engineering knowledge
  • Organization requires real-time analytics on streaming data rather than batch query-based analytics
  • User lacks access to supported data warehouses (BigQuery, etc.) or cannot integrate with dbt, Looker, or Notion
  • Team needs out-of-the-box dashboards and pre-built reports without building custom agent context
  • Organization cannot self-host or use cloud infrastructure and requires on-premise deployment without internet connectivity
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Pricing

Freemium with self-hosted free tier, cloud-hosted paid tier, and enterprise custom pricing View pricing