nao

nao is a revolutionary AI code editor built from the ground up for data professionals. It aims to accelerate the entire data workflow, from writing code to deploying pipelines, by integrating deeply with your data ecosystem. Designed for data analysts, analytics engineers, data scientists, and data engineers, nao acts as an intelligent partner, understanding the context of your data to help you write code that is not only syntactically correct but also semantically sound and safe for your production environment.

Unlike generic AI code assistants, nao connects directly to your data warehouse (supporting platforms like Databricks, DuckDB, and more). This native integration allows its AI to be 'data-aware,' providing suggestions based on your actual schema, table structures, and column names. This eliminates guesswork and significantly reduces errors. The core of nao is its powerful AI agent, which goes beyond simple code completion to become a guardian of your data quality.

How to use nao

Getting started with nao is a straightforward process designed to integrate seamlessly into your existing workflow:

1. Download and Install: Begin by downloading the nao IDE for free from the official website. It's a standalone application that runs on your local machine.
2. Connect Your Data Warehouse: The first crucial step is to connect nao to your data source. This secure connection allows the AI to access your schema metadata (not your actual data, which stays local) to provide context-aware assistance.
3. Start Coding: Open a SQL worksheet or a Python script. As you type, nao's AI provides intelligent auto-completion for SQL queries and dbt models, aware of your specific tables and columns.
4. Leverage the AI Agent: Use the dedicated AI tab to interact with the agent. You can ask it to generate complex queries, create dbt models, write documentation, or add tests. The agent understands your project's context, including dbt models and column-level lineage.
5. Preview and Diff: Before committing any changes, use the 'Instant Diff Preview' feature. This shows you the direct impact your new code will have on the data, helping you catch potential issues and prevent breaking downstream dashboards or reports.
6. Run Checks and Deploy: The agent can run data quality checks and your existing tests to validate your code. Once you're confident, you can ship your data pipelines faster and with greater confidence.

Core Features of nao

• AI-Powered Code Editor: Optimized for SQL and Python with smart auto-completion, code generation, and conversational analytics capabilities.
• Native Data Warehouse Integration: Connects directly to your data sources like Databricks and DuckDB for schema-aware AI suggestions.
• Advanced AI Agent: A multifaceted agent that assists with data quality checks, instant data diffs, running tests, and understanding column-level lineage.
• Deep dbt Integration: Preview dbt models directly in the IDE, get auto-complete for model columns, and visualize the lineage graph to understand dependencies.
• Instant Diff Preview: See the impact of your code changes on the data in real-time, preventing unintended consequences.
• Conversational Analytics & Charts: Interact with your data using natural language to generate insights and visualizations directly within the editor.
• Enterprise-Grade Security: Your data and code remain local. Nothing is shared with an LLM without explicit permission, and enterprise plans offer options for self-hosted LLMs to keep everything within your infrastructure.
• Unified Development Environment: Combines the tools you love—SQL editor, transformation tool (dbt), and BI lineage—into a single, cohesive IDE.

Use Cases for nao

nao is versatile and can be applied to numerous data-related tasks:

• Accelerated Data Pipeline Development: Rapidly build and iterate on SQL and Python pipelines with AI-generated code and instant feedback.
• Robust dbt Workflow Management: Create, test, and document dbt models more efficiently. Understand the impact of changes with column-level lineage and model previews.
• Complex Data Analysis: Perform sophisticated analyses such as distribution, retention, conversion, and root cause analysis using conversational prompts and powerful querying tools.
• Data Quality Assurance: Proactively identify and fix data quality issues before they affect production by using the agent's automated checks and data diffs.
• Safe Code Refactoring: Confidently refactor complex SQL queries or dbt models, using the instant diff preview to ensure the output remains consistent.

Advantages of nao

nao offers significant advantages over traditional code editors and other AI assistants:

• Data-Aware Intelligence: Unlike tools like Cursor, nao's suggestions are not generic; they are tailored to your specific data schema, resulting in code that works correctly the first time.
• Enhanced Safety and Reliability: The focus on data quality checks, diffs, and lineage impact analysis helps prevent data breakages, protecting your BI dashboards and analytical reports.
• Increased Productivity: By unifying multiple tools into one IDE and automating repetitive tasks, nao allows data teams to ship projects significantly faster.
• Uncompromised Security: With a strong emphasis on data privacy, nao ensures your sensitive data and proprietary code are secure, offering enterprise-level controls for maximum protection.

Pricing and Plans

nao offers a flexible pricing structure to suit different needs:

• Starter Plan: Free. This plan includes a 15-day trial of the Pro features, basic data warehouse connection, SQL auto-complete, and dbt previews & lineage.
• Pro Plan: $30 per user/month. Includes everything in the Starter plan, plus the full AI tab on your data, the complete AI agent for data workflows, instant data diff, and direct support.
• Enterprise Plan: Custom pricing. This plan includes all Pro features, plus enterprise-grade data security, the option for enterprise-hosted LLMs, an enterprise workspace, and a dedicated support team.