Querio

Querio is a data platform designed to enable teams and customers to explore data directly without relying on technical gatekeepers. It combines agentic notebooks with governed AI agents, allowing users to ask natural language questions and receive transparent, context-backed answers in the form of SQL queries or Python code. The platform’s core functionality revolves around a reactive notebook environment where cells automatically update when underlying data changes, supporting iterative analysis and real-time collaboration. Users can pose questions like “How did churn change last quarter?” and the system generates executable SQL or Python logic, complete with tables or visualizations, while preserving the original business context. This design helps data teams delegate routine inquiries to non-technical stakeholders, reducing ad-hoc requests and freeing analysts for deeper work. Querio also offers forecast revenue modeling, churn analysis, and custom metrics defined through natural language. Context management is a key feature: administrators can set governed context—such as business definitions, data mappings, and access controls—so that every AI-generated response remains accurate, secure, and aligned with company policies. The platform integrates with common data sources and supports role-based permissions, allowing data teams to maintain oversight while enabling self-service for sales, marketing, product, and customer success departments. Querio’s notebook interface also supports reactive cells that recalculate automatically, making it suitable for live dashboards and recurring reports. For advanced users, it provides direct interaction with Python and SQL code, while non-technical users can stay in conversational mode. The underlying AI agent interprets questions