nao

About nao

nao is an AI-powered data IDE built for analysts, engineers, and data scientists to write SQL, Python, and dbt workflows. It connects directly to your warehouse and reads schema and metadata so teams can preview changes, catch issues early, and deploy with greater confidence.

Review

nao combines a code-centric editor (a fork of VSCode) with direct warehouse connectivity and an AI assistant that has access to code, metadata, data stack and business definitions in a local-secure setup. The result is an environment that brings editing, testing, lineage previews, and deployment into a single place, reducing the number of tools data teams need to juggle.

Key Features

• AI-assisted authoring for SQL, Python, and dbt with context from schema and docs
• Direct connection to your data warehouse with schema awareness and lineage previews
• Preview diffs and environment switching (dev → staging → prod) to catch breaking changes early
• Integrated testing and quality checks with linkbacks to sources and generated dbt models/tests
• Collaboration-friendly workflows that reduce context switching between IDE, warehouse console, and BI tools

Pricing and Value

nao offers a free tier to try core functionality and get a feel for the editor and AI features. Paid tiers (Pro and Enterprise) unlock advanced capabilities such as enterprise security options, Bring-Your-Own-Key (BYOK) for model access, and dedicated support. For teams that maintain data pipelines and want fewer integration gaps, nao can provide strong time savings and fewer production incidents; organizations with minimal data engineering needs may find the free tier sufficient to evaluate fit.

Pros

• Deep warehouse integration and schema-aware AI make it easier to write correct queries and models
• Combines multiple steps (authoring, previews, tests, deployment) into one editor, cutting down tool-switching
• Lineage and diff previews help catch logical issues before they reach production
• Familiar VSCode-like interface lowers the barrier for engineers and analysts who already use code editors

Cons

• The SQL editing experience may still lag behind specialized SQL IDEs for advanced query tuning or database-specific features
• Enterprise features such as BYOK and bespoke security setups are gated behind higher tiers
• Adopting an integrated IDE requires some process change for teams used to separate consoles and BI tools

nao is a strong fit for data teams that build and maintain pipelines, use dbt or similar tooling, and want to consolidate code, tests, and lineage checks into a single workflow. It makes the most sense for teams that value tighter warehouse integration and AI-assisted context over using a piecemeal set of tools; smaller teams can start on the free tier to determine whether it aligns with their needs. Learn more or try it at getnao.io.

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