Querio

Querio is a git-native analytics product from Querio Ltd. It lets people and AI agents work on the same analytics stack, from data models to dashboards, with business context stored as code in a git repository the customer owns. The company's homepage also announces a $5M raise.

What It Is

Querio is an AI analytics platform that connects to a data warehouse and lets users ask questions, analyze data in notebooks, and publish dashboards and reports. Its shared context layer holds metadata, semantics, metric definitions, business rules, memory, skills, and automations, kept in a git repo and synced with dbt models so both can be updated in one pull request. Querio says every agent and tool reads the same definitions, so a metric means the same thing wherever it is queried.

How the Workflow Looks

In the product demo, a user prompts the AI to build an executive board. The agent calls tools, uses context files such as skills, catalog definitions, and SQL models, and produces KPI tiles, a SQL-backed data table, and charts in a notebook or layout view. Users can then refine individual cells with follow-up prompts and slash-command skills. Automations can run a prompt on a schedule and send the result by email, and reports can be shared by link.

Agent and Developer Access

Beyond the web app, data can be queried through MCP, Slack, a CLI, an API, or an IDE, all backed by the same context. Querio describes per-user authentication, a governed runtime, shared outputs, and audited questions. A sample MCP configuration points at Querio's HTTP MCP endpoint with a bearer token.

Embedded Analytics and Security

Teams can white-label Querio inside their own product using SSO embedding, APIs, and the MCP server. Customization uses CSS, HTML, and chart themes, and row-level security scopes each customer's data. The company lists role-based access, audit logs, no training on customer data, and private deployment, and displays SOC 2, GDPR, and CCPA badges. It also states HIPAA and ITAR compliance.