What is nao?
Working with data often involves intricate coding tasks – preparing transformations, writing complex queries, ensuring data quality, and documenting everything meticulously. You know your data best, but translating that knowledge into accurate, efficient code can be time-consuming, involving slow feedback loops and repetitive work. nao is an intelligent code editor specifically designed for data teams like yours, integrating AI assistance directly into your daily workflows. It helps you write better code, faster, by understanding the unique context of your data environment.
What nao Offers Your Data Team
🤖 Leverage a Data-Aware AI Agent: Interact with an AI assistant specifically trained on core data workflows. It excels at tasks like preparing data with dbt, crafting SQL queries, implementing data quality tests, and generating documentation, understanding the nuances of data work.
🔗 Connect Natively to Your Data Warehouse: nao integrates directly with your existing data infrastructure, including platforms like BigQuery, Databricks, Iceberg, PostgreSQL, and Snowflake. This means the AI agent generates code that is aware of your specific schemas and data structures, significantly improving relevance and accuracy.
📊 Preview Data Directly in the Editor: See samples and results of your data transformations right alongside your code. This immediate feedback eliminates the need to constantly switch tools, keeping you focused and accelerating your development process.
⚡ Visualize Code Impact Immediately: Understand how your code modifications affect the data in near real-time. This rapid feedback cycle helps you catch errors early and iterate more quickly than traditional development loops allow.
✅ Automate Complex Data Checks: Delegate the execution of intricate data quality checks to the nao agent. Define your criteria, and let the AI handle the verification while you concentrate on the next task.
See nao in Action: Practical Use Cases
Accelerating dbt Model Development: You're building a new dbt model. Instead of writing boilerplate SQL or documentation from scratch, you prompt the nao agent. Because it's connected to your warehouse, it generates accurate
ref()functions, suggests relevant column descriptions based on your schema, and even drafts initial data quality tests specific to your tables. You review, refine, and commit much faster.Streamlining Data Quality Assurance: Before deploying a critical pipeline update, you need to ensure data integrity. You define several quality rules (e.g., checking for nulls in key columns, validating formats, ensuring referential integrity). You then ask nao's agent to write and execute these checks directly against your staging data, getting immediate confirmation or identifying specific issues within the editor.
Optimizing Ad-Hoc Analysis: A stakeholder asks for a complex analysis requiring joins across multiple tables and specific filtering logic. You describe the required output to the nao agent in natural language. It generates the SQL query, which you can immediately run and preview the results for within nao. You can then iteratively refine the query with the agent's help until the analysis is perfect.
Get Started with Smarter Data Coding
nao is built to enhance the capabilities of data professionals, not replace them. By providing an AI assistant that genuinely understands your data and workflows, it aims to remove friction, reduce repetitive tasks, and shorten the time between idea and implementation. Spend less time wrestling with code syntax and feedback delays, and more time delivering valuable insights.
Ready to experience a more intuitive way to work with data?
Join the waitlist today.
More information on nao
Launched
2024-07
Pricing Model
Free Trial
Starting Price
$30 /month
Global Rank
Follow
Month Visit
<5k
Tech used
Plausible Analytics,OpenGraph,Nginx
nao was manually vetted by our editorial team and was first featured on 2025-04-22.
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