Introducing MetricWise: a BI tool with a metrics layer

MetricWise is a BI tool with a governed metrics layer.

It helps teams define trusted metrics once, then use them across dashboards, visual exploration, and AI analytics. Instead of every dashboard having its own version of the truth, MetricWise gives your team one approved layer for the numbers that matter.

I’ve been building it over the last few months, and it’s now ready to try.

Most BI tools make it too easy for metric logic to spread everywhere.

One team defines active users one way. Another team defines it slightly differently. A third dashboard uses its own SQL. Nobody notices until two reports show different numbers for the same metric.

AI can make this worse. If you point an AI tool at raw warehouse tables, it can produce SQL that looks right but gives the wrong answer.

MetricWise is built around a simple idea: define important metrics once, govern them properly, and make every workflow use those definitions.

MetricWise lets you build semantic models from your warehouse tables.

You can define dimensions, measures, and joins in a visual editor or directly in a DSL. You can switch between both as needed.

Before a model goes live, MetricWise validates it and shows diagnostics, so you can catch issues early.

Users can ask questions in plain English.

MetricWise answers using semantic models that admins have approved for AI Search. Users can choose the model scope, view history and settings, and save generated dashboard artifacts into the Library.

The goal is simple: AI answers should come from governed metric definitions, not guesses against raw tables.

For everything else, there is Visual Explore.

Pick dimensions and measures. Add filters and date controls. Run the query. Inspect the SQL and results. Then customize the chart and save it as a reusable chart, dashboard tile, or metric view.

Create dashboards and folders. Search, sort, and filter Library items. Manage private and shared assets separately.

You can drag and resize tiles, add dashboard filters, duplicate dashboards, copy links, and open any tile back in Explore when you want to keep working on it.

MetricWise includes a catalog for shared and private metrics.

You can browse metrics, view their canonical definitions, save your own views, turn those views into charts, and add them to dashboards.

The point is to make it clear which number is the right one before it becomes a meeting debate.

MetricWise also supports GitHub source control for semantic model changes.

Connect a repo and branch, see which model files were added, changed, or deleted, write a commit message, and push the update.

Private dashboards and charts are excluded from sync, so personal work does not accidentally end up in production.

MetricWise currently supports BigQuery service account connections, Google Sheets, and file style connections.

You can test connections, refresh schemas, select visible tables, and control field visibility.

Snowflake is visible in the app, but marked “Soon” while it is being finished.

MetricWise supports Google sign in, workspaces, workspace switching and creation, member invites, role changes, and removals.

Admins can also manage plan details, query defaults, theme settings, and which models AI Search is allowed to use.

MetricWise is now open to first customers.

If your team wants a BI tool with governed metrics, visual exploration, dashboards, AI analytics, and source control for your metrics layer, get in touch.

MetricWise: BI Tool with Governed Metrics