nao

4.40

RATING

254 M+

EXPOSURE

About this tool

Name

nao

Category

tools

nao is an AI-powered data editor designed specifically for data teams, offering a seamless way to edit, fix, and transform data while staying connected to your warehouse and real business context. Its intelligent agent writes code with data quality in mind — generating SQL, cleaning messy fields, fixing inconsistencies, and applying transformations safely and transparently. Instead of juggling dashboards, ad-hoc scripts, and endless reviews, nao provides a unified workspace where AI accelerates the heavy lifting while humans stay in control. Simply put, it’s the best way to work on data with AI: fast, safe, context-aware, and built for real data operations.

Ratings and Reviews

Game-changing for data cleanup

4.60

nao fixed inconsistent fields and generated reliable SQL faster than our team could draft manually. The data quality improvements were instant.

August 28, 2025

Lucas Brennan

Perfect blend of AI speed and human control

4.40

I loved how nao understood business context before applying transformations. It made AI outputs far more trustworthy.

September 12, 2025

Melissa Grant

Very useful but requires warehouse setup

4.20

Once connected, it worked beautifully. The only challenge was aligning permissions and connecting the warehouse initially.

October 8, 2025

Hiro Tanaka

Huge productivity boost for our data team

4.50

The AI-generated SQL was clean, accurate, and easy to validate. It saved hours on repetitive data-fixing tasks every week.

October 30, 2025

Ariana Flores

Reliable and context-aware

4.30

The agent understood our domain-specific rules and suggested high-quality fixes. Looking forward to more automation features.

November 19, 2025

Daniel Hoffman

How to use

Open the nao platform and connect your data warehouse to enable real-time access Select the dataset or table you want to work on and describe the issue or transformation Let nao’s AI agent generate SQL, fixes, or transformations based on your business context Review, refine, or approve the proposed changes before applying them to your environment Track edits, monitor data quality improvements, and continue iterating with AI assistance

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