nao Labs is an AI-powered code editor designed specifically for data teams, enabling users to write, test, and maintain data-centric code more efficiently. nao Labs integrates directly with data warehouses and is trained on real-world data workflows, allowing its AI agent to generate code that is tailored to a team's actual data and ensures high-quality output.
How does nao Labs help data teams?
the core product, nao, functions as an AI code editor that assists data teams in various tasks, including:
- Generating SQL queries and dbt models directly from data warehouse tables
- Adding documentation and tests to data assets
- Refactoring codebases using data lineage
- Performing data quality checks and data diff tests
- Enabling conversational analytics through natural language prompts
The nao AI agent is natively integrated with data warehouses, meaning it can only suggest code and provide insights based on the specific tables, columns, and data present in the user's environment. This approach reduces errors and accelerates the development of reliable data workflows.
What makes nao Labs different?
Unlike general AI code editors, nao Labs is purpose-built for data professionals, focusing on:
- Native integration with data warehouse environments
- AI suggestions that are aware of actual, live data structures
- Automated testing and documentation for improved data quality
- Streamlined workflows for creating, refactoring, and maintaining analytics code
Who uses nao Labs?
nao Labs is targeted at data teams, including data engineers, analytics engineers, and data scientists working in organizations that rely on modern data warehouses. The tool is designed for businesses looking to increase the speed and reliability of their data operations. While specific customer names are not publicly listed, the product is positioned for startups, scale-ups, and enterprise data teams aiming to improve code quality and workflow efficiency.
How was nao Labs started?
nao Labs was founded by Claire Gouze (Co-founder & CEO) and Christophe Blefari. Claire Gouze brings experience as head of data at Sunday (a company with a $100M Series A) and a background in data science from BCG Gamma. Christophe Blefari has built data tools and teams across more than 10 organizations, including scale-ups and government projects, and is an active writer on data topics. Their combined expertise in building and scaling data platforms informed the creation of nao Labs to address the unique challenges of data engineering and analytics workflows.
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