Description
Querio is a next-generation data platform designed to empower data leaders, teams, and customers with self-serve analytics. It leverages best-in-class AI agents and governed context to make data exploration accessible at any technical level. Users can ask questions directly against existing logic, and Querio provides instant insights with transparent SQL or Python code backing every response.
The platform's core innovation lies in its reactive notebooks, which function like spreadsheets with cells that recompute automatically when dependencies change. These notebooks are built for SQL and Python, offering a flexible coding environment for all analytics work. Unlike traditional Jupyter notebooks, Querio's notebooks are designed for AI analytics, powering every output, interface, and interaction. Every AI query is explicit code that users can read or edit, fostering transparency and collaboration.
Querio also facilitates the creation and sharing of beautiful, automatically refreshing boards. These boards are collections of notebook cells, allowing users to curate and present insights effectively. An AI chat sidebar is always available for quick changes or new questions, streamlining the process of creating perfect reports in minutes. Boards stay up-to-date by automatically re-running cells, with easy-to-setup scheduling. Verified boards offer a clear distinction between data team-reviewed content and one-off reports.
The platform emphasizes the importance of context for reliable AI. Querio's context layer allows users to define and build up important logic as they work. This context is versioned by default, self-healing over time, and managed through a flexible file system. Querio can be embedded anywhere, including internal tools, products, and MCPs, making data value accessible to a wider audience. The company highlights significant benefits for adopting teams, including reduced hiring needs, saved employee time on analysis, and faster reporting cycles, often by replacing existing BI tools.
Querio connects directly to various data sources with industry-leading security and governance. Supported data sources include BigQuery, Snowflake, MotherDuck, Redshift, ClickHouse, PostgreSQL, MySQL, MariaDB, and Microsoft SQL Server. The platform aims to make everyone a data person by providing an intuitive and powerful way to interact with data.
Querio's Core Features
Agentic notebooks for data exploration
Transparent SQL and Python backed responses
Reactive cells that recompute automatically
Flexible coding environment for SQL and Python
Collaborative notebook editing and building
Publishable boards for curated insights
AI chat sidebar for quick queries
Context layer for reliable AI
Versioned and self-healing context
Embeddable analytics into any platform
Direct data source connections
Verified boards for reviewed insights
How to use Querio?
Configure: Connect your data sources and define your context layer.
Explore: Ask questions using natural language or code in agentic notebooks.
Iterate: Use the AI chat sidebar for quick changes and deeper dives.
Share: Create and publish curated boards for easy reporting.
Embed: Integrate Querio insights into your internal tools or products.
Querio's Use Cases
- Self-Serve Analytics
- Instant Insights
- Transparent Data Exploration
- Collaborative Analysis
- Interactive Reporting
- Embedded Analytics
- Context-Aware AI
- Data Governance
