Fit with your data stack

Querio brings analysis and reporting into the way your data team already works: SQL and Python, Git, and agents that help you build.

Keep your warehouse and dbt models. Bring the context behind your analytics into the same project, then give your whole team a way to work with the results.

One project, a shared workflow

Your models, business definitions and analytical work are closely connected. They should be easy to develop and review together.

You can keep your dbt project and Querio context in the same repository:

analytics/
  dbt/
  querio/
  querio.toml
  .github/workflows/

That gives your team one place to work on transformations and the guidance behind your analysis. A change to a revenue model and its business definition can go through the same pull request.

Connect GitHub and configure CI sync to bring reviewed context changes into Querio.

Set up Git and CI sync

Build on what you've defined in dbt

Querio queries your dbt models through the database or warehouse where they're built. Your existing transformations and tests remain part of your data pipeline.

Use the descriptions, SQL and business rules in your project as the starting point for Querio's context. A coding agent working in the repository can help adapt that knowledge into the files Querio uses.

Keeping those files alongside dbt lets you review changes together as your models evolve.

For example, your orders model might define which transactions count as revenue. Querio context can explain how your team uses that model, which reporting periods matter and how to handle refunds.

Context and accuracy

Work from your preferred interface

Use the browser for interactive analysis, boards and conversations. Use the CLI from your terminal or coding agent to work with notebooks and workspace files. Connect Claude or ChatGPT through MCP to analyze data from your AI assistant.

These are different ways into your Querio workspace. Roles, groups and datasource permissions govern access.

Get started with CLI | Get started with MCP

Bring your existing BI work

Your existing BI tools hold useful definitions, queries and reporting logic.

unshackle exports that work into files in Git. A coding agent can then use Querio CLI to adapt it into Querio context and notebooks.

Start with one report. Review unfinished translations, compare the results with the original, and build from there.

Move BI work into Querio

Give the whole team a way in

Your data team can work in code and Git while colleagues explore boards, ask follow-up questions and receive scheduled reports.

The work you maintain in your data project becomes something the rest of the company can use, without needing to navigate that project themselves.

Try it on a question you know

Choose a familiar business question. Use your existing models and definitions, inspect the analysis, and compare it with a trusted result.

Then share it with a colleague. Can they understand the answer, ask another question and keep exploring?

Get your first answer on your data

For security review and supporting documents, visit the Trust Center.