LogicGate

What the problem was

Dashboards disagree. Not because the data is wrong, but because the definitions are.

In my experience working with data teams, “active customer” or “MRR” often lives in old SQL queries, dashboards, and Slack or WhatsApp threads. Change a filter and nobody knows who did it or why. Business stakeholders can’t read the logic, so they just have to trust it.

Day to day, that looked like this:

• Every stakeholder had their own version of the logic.
• Nothing was documented anywhere.
• Definitions changed daily, verbally or in chat.
• Nobody knew which version was “current”, or who approved it.
• So the same metric came out different in every dashboard.

The engineers in the middle were left guessing, rewriting SQL every time the “rules” moved. The problem was never the data. It was that the business logic had no home.

How I solved it

LogicGate is that home:

• Visual definitions: stakeholders define metrics and rules visually, with no code.
• Versioned changes: every change is versioned, with a reason, an author, and a diff.
• Approvals: critical changes need an approver before going live.
• Discussion in context: conversations happen on the definition, not in a chat thread that disappears.
• Compiles to code: each definition compiles automatically to SQL, Python, or dbt.
• One source of truth that business and engineering can both read.

Walkthrough

Try it at logicgate.space, or watch the 3-minute walkthrough on Loom.

Stack

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