Install: Download and install nao from the official website.
Connect: Link nao to your data warehouse (Postgres, BigQuery, Snowflake, etc.).
Index (optional): Let nao index your codebase and warehouse schema so the AI agent gains full context.
Write with assistance: Use the built-in AI-powered Code Assistance to write SQL, Python, or dbt workflows, with auto-completion based on your real schema.
Use AI agent: Ask the agent to build pipelines, generate dbt models, run analytics, and create documentation or tests.
Preview & QA: Preview query results, run data-quality checks, compare dev vs production data (data diff), and inspect lineage before deploying.
Collaborate (teams): If you are working in a team, leverage multi-seat plans and shared workspace.
Stay secure: All data stays local; only non-sensitive metadata is used for AI — your data never leaves your warehouse unless you authorize it.
Start free: Try the free tier; upgrade to Pro or Enterprise when you need more capacity or team features.
Nao is quickly establishing itself as one of the most impactful AI tools in the data engineering and analytics space, offering a remarkably smooth workflow from installation to daily production use. What makes nao stand out is not only its advanced Code Assistance, but also the fact that every step of using the platform is designed to enhance accuracy, speed, and trust across data teams.
Getting started with nao is effortless. After installing the application from the official website, users can connect it directly to their data warehouse—whether they work with Postgres, BigQuery, Snowflake, or a modern lakehouse environment. This immediate integration is what allows nao to deliver schema-aware intelligence, making it far more effective than generic AI tools that operate without real data context.
One of nao’s defining strengths is its optional indexing feature. Allowing nao to index your codebase and warehouse schema gives the AI agent complete project awareness. This unlocks a level of Code Assistance that feels truly collaborative: auto-complete based on actual tables, SQL generated specifically for your models, and AI suggestions that reflect your organization’s real data structure.
Once set up, users can write SQL, Python, or dbt workflows with nao’s intelligent AI agent guiding the process. Whether you need to build data pipelines, generate dbt models, or run complex analytics, nao functions like an expert teammate that understands both your code and your data. It can even create documentation, tests, and quality checks automatically — a massive advantage over AI tools that only produce code snippets without validating them.
Before deploying, users can preview query results, run data-quality checks, compare development and production tables, and inspect lineage. This ensures that every change is safe and that no downstream dashboards or models break.
Nao also supports team collaboration via multi-seat plans, making it easy for organizations to standardize AI-powered development. Security remains first class, with data staying local and only non-sensitive metadata ever being shared.
For anyone wanting to experience a modern, secure, and context-aware AI tool for data work, nao’s free tier provides the perfect starting point. It is a unique blend of powerful Code Assistance and warehouse intelligence that redefines what an AI tool can do for data teams.