# Nao AI data editor

## About

nao Labs — Do. Data. Faster. With the first AI data editor that understands data work.

- Verified: Yes

## Services

### Data Governance & Analytics
- [Data Management & Analytics](https://bilarna.com/services/data-governance-and-analytics/data-management-and-analytics)

### Data Security & Privacy
- [Data Security and Privacy](https://bilarna.com/ai/data-security-and-privacy/data-security-and-privacy)

## Pricing

- Model: custom

## Trust & Credentials

### Certifications
- SOC 2 (SOC2)
### Compliance
- SOC2
### Data Security
- SOC 2

## Frequently Asked Questions

**Q: What features should I look for in an AI-powered data editor for data teams?**
A: An AI-powered data editor for data teams should offer seamless integration with various data warehouses such as Postgres, Snowflake, BigQuery, and others. It should provide an intuitive interface where users can query data directly, with features like SQL worksheets, table and column auto-completion, and cost estimation for queries. Additionally, the AI agent should have direct access to the data schema to write accurate code, analyze data quality, and assist with data visualization. Integration with data stack tools like dbt and the ability to personalize AI behavior based on project rules are also important. Finally, strong data security measures, including local data connections and compliance certifications, are essential to protect sensitive information.

**Q: How does an AI data editor ensure data security and privacy?**
A: An AI data editor ensures data security and privacy by establishing local connections directly between the user's computer and their data warehouse, meaning no data is sent externally unless explicitly permitted. This approach prevents sensitive information from being transmitted to third parties or used for AI training without consent. Additionally, compliance with security standards such as SOC 2 Type II certification guarantees that the platform adheres to rigorous privacy and security protocols. These measures collectively protect data from unauthorized access, maintain confidentiality, and provide users with control over their data, ensuring that privacy is never compromised during AI-assisted data work.

**Q: How can AI integration improve the workflow of data teams working with SQL and data warehouses?**
A: AI integration can significantly enhance the workflow of data teams by providing intelligent assistance directly within their development environment. Features such as AI-powered auto-completion for tables and columns speed up query writing and reduce errors. The AI agent’s ability to understand the data schema allows it to generate accurate SQL code, analyze data quality, and suggest relevant queries or visualizations. Integration with multiple data warehouses enables seamless querying across platforms without switching tools. Additionally, AI can help manage and preview dbt models, view data lineage, and incorporate project-specific rules to personalize coding styles. These capabilities streamline data exploration, improve productivity, and enable faster, more reliable insights.

## Links

- Profile: https://bilarna.com/provider/getnao
- Structured data: https://bilarna.com/provider/getnao/agent.json
- API schema: https://bilarna.com/provider/getnao/openapi.yaml