About ClariLayer
We spent years watching metric drift derail executive decisions at high-growth technology companies. ClariLayer exists because someone got tired of the 45-minute audit.
Every modern data team has invested in warehouses, semantic layers, and BI tools. But there is a critical gap in this stack: no tool captures the business context behind the numbers.
What does this metric mean? Who approved it? Which version is current? When should an AI agent trust it? This context lives in Slack threads, Confluence pages, and the heads of senior analysts. It evaporates when people leave. It drifts when teams grow.
We watched this play out at scale. Two VPs show up to a board meeting with different revenue numbers. 45 minutes spent auditing the slide instead of making decisions. Trust breaks, executives revert to gut-feel, and the million-dollar data stack becomes expensive shelf-ware.
With AI agents now making autonomous decisions based on metric definitions, the stakes are even higher. An agent that uses the wrong churn definition does not raise its hand and ask for clarification. It acts, confidently and incorrectly.
ClariLayer is the context layer for business metrics. It sits alongside your warehouse and semantic layer, capturing the meaning, ownership, approval status, and trust signals that no other tool records.
Business users define metrics in natural language. AI structures them into governed definitions. Validation probes verify logic against your actual warehouse data. Tier-based governance matches rigor to stakes. And the Contract API gives AI agents, dashboards, and internal tools a formal interface to query the governed truth.
We are not replacing your warehouse or your semantic layer. We are adding the missing layer between them and the humans and AI agents that consume their output.
ClariLayer works with any warehouse, any semantic layer, and any AI framework. No vendor lock-in. The Switzerland of metric governance.
The people who own metric meaning should be able to define and update it without a Jira ticket or a SQL editor.
Every definition has a version, an owner, an approval chain, and a conversation audit trail. Trust is earned, not declared.
We did not bolt on AI agent support as an afterthought. The Contract API was designed for the world where AI agents make autonomous decisions.
If your organization struggles with metric trust, definition drift, or AI agents acting on ungoverned data, we would love to talk.
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