RevOS Metric Store: One definition of every metric, for people and AI agents

Ask four systems for ARR and you get four numbers. RevOS Metric Store gives every metric one definition, written as code in your semantic model. Dashboards, BI tools and AI agents like Claude and ChatGPT all read the same one. Now in beta.

Hi Product Hunt, Renat here, founder of RevOS.

Every customer and revenue leader we speak to tells the same story. They start using AI on their data, ask an important question and get a plausible-looking wrong answer, very fast. Then three people spend a week explaining where the number came from, and after that nobody trusts the AI answers. Winning that trust back takes a huge effort.

The model is rarely the problem. Most data was never structured for AI: the same metric means something different in the CRM, the spreadsheet and the BI tool, so the agent picks one.

So we built the Metric Store:

every metric gets one definition, written as code in your semantic model
you can see exactly how each number is calculated, and everywhere it's used
dashboards, BI tools and AI agents like Claude and ChatGPT all read that same definition

It makes a measurable difference: a general model scored 51% on raw schemas and over 90% with a semantic model.

We're in beta. If you want to see it on your own metrics, book a demo from the link above. I'm here all day to answer questions.

Which metric does your team argue about most?

Pavel from the RevOS engineering team here.

Quick technical note: every metric is defined as code in our semantic model, and changes are reviewed through a pull request. Composite metrics, like a ratio built from two other metrics, show exactly which metrics they’re made of, so you can see how a number is built.
Happy to answer any technical questions today!

Lev from the RevOS team here. My favorite bit is a small one: open any metric and you see exactly how it's calculated and every dashboard that uses it. "Why is this number different?" becomes a 10-second check instead of a meeting.