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nao Labs - Cursor for data

AI code editor to write code on your data — and trust the output.

🥷 Manifesto

Data teams have been left out of the vibe coding party. We’re building nao so they can data vibe too.

🏎 TL;DR

nao is an AI code editor to write code on data: a local editor, connected to your data warehouse, with an AI copilot that has context of both your data schema and codebase.
It’s built specifically for data workflows - helping teams write faster, better code, while being ensured of the data quality.

🧑‍💻 Who is it for?

  • Data teams who run analytics with SQL and build dbt or Python pipelines
  • Software developers who manage SQL databases

🤖 What can you do with nao?

You can prompt nao AI agent to:

  • Create SQL queries & dbt models from your data warehouse tables
  • Add documentation & testing to your data
  • Refactor your codebase through your lineage
  • Perform data quality checks, data diff tests
  • Run conversational analytics

nao AI tab auto-suggests code for your data — only with tables, columns and data that actually exist in your warehouse.

🔆 Why we built it

Christophe and Claire have each spent 10 years in data. We’ve seen that data teams can’t keep the business pace because making changes in data requires too many tools and tests.
Current AI code editors don’t interact natively with data warehouses — they autocomplete SQL blindly, not knowing your data schema. We built nao so that data teams can ship at business pace, with an AI code editor that has all their context.

👀 Watch it live

https://www.youtube.com/watch?v=QmG6X-5ftZU

👋🏻 Our ask

Want to write code on your data faster?