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.
Hi Product Hunt, I’m Claire, co-founder of nao Labs! 👋🏻
nao is the AI data IDE I wish I had when I was working in data.
2 years ago I was head of data at sunday. I was trying to keep up with the speed of the business, helping my team avoid breaking changes in prod, while trying to save them time for the interesting analytics stuff.
But it was tough. Our tools just seemed so unadapted to our work. We kept switching from the IDE to the warehouse console and manually applying data model changes in the BI tool. I kept reconnecting extensions until I just gave up.
Then AI came!
But once again, AI coding tools were thought for developers, not for data people. They handle code context very well, but not the variety of context you need for data work: data schema, documentation, data stack, business definitions.
So one year ago, when Christophe and I started thinking about how to make data tooling more efficient for data people, it became clear: we wanted to create the best place to work on data with AI.
nao is the AI data IDE, designed specifically for data workflows. It’s a fork of VSCode, directly connected to your warehouse. And the AI agent has all the context of your code + metadata + data stack and business context - all in a secure local setup.
We released our first version 6 months ago, so I can tell you a bit about what our users love:
It’s all in one. Anyone in the data team - technical or not - can easily connect their data and stack integration in one click.
One prompt from data schema to a full data pipeline with data quality checks.
One prompt for deep-dive analysis. nao plans analytics to run, runs all checks, and provide a full analytics summary.
nao is still in beta and there’s much more coming. Our goal is to be fully integrated across your entire data stack, end-to-end — from data engineering to data science to analytics. We believe that for AI to be adopted in analytics, it must first be adopted and trusted by the data team itself.
We have a free trial and free version - give it a try and let us know what you think!
Hi Product Hunt, I’m Claire, co-founder of nao Labs! 👋🏻
nao is the AI data IDE I wish I had when I was working in data.
2 years ago I was head of data at sunday. I was trying to keep up with the speed of the business, helping my team avoid breaking changes in prod, while trying to save them time for the interesting analytics stuff.
But it was tough. Our tools just seemed so unadapted to our work. We kept switching from the IDE to the warehouse console and manually applying data model changes in the BI tool. I kept reconnecting extensions until I just gave up.
Then AI came!
But once again, AI coding tools were thought for developers, not for data people. They handle code context very well, but not the variety of context you need for data work: data schema, documentation, data stack, business definitions.
So one year ago, when Christophe and I started thinking about how to make data tooling more efficient for data people, it became clear: we wanted to create the best place to work on data with AI.
nao is the AI data IDE, designed specifically for data workflows. It’s a fork of VSCode, directly connected to your warehouse. And the AI agent has all the context of your code + metadata + data stack and business context - all in a secure local setup.
We released our first version 6 months ago, so I can tell you a bit about what our users love:
It’s all in one. Anyone in the data team - technical or not - can easily connect their data and stack integration in one click.
One prompt from data schema to a full data pipeline with data quality checks.
One prompt for deep-dive analysis. nao plans analytics to run, runs all checks, and provide a full analytics summary.
nao is still in beta and there’s much more coming. Our goal is to be fully integrated across your entire data stack, end-to-end — from data engineering to data science to analytics. We believe that for AI to be adopted in analytics, it must first be adopted and trusted by the data team itself.
We have a free trial and free version - give it a try and let us know what you think!
Happy data vibing,