An AI agent pointed at raw tables has to guess: which column is revenue, what timezone, which rows is this user allowed to see. That is exactly where ungoverned AI goes wrong.
SemanticFed is designed to be the layer an agent queries instead. It exposes documented entities and metrics with types and descriptions, and it enforces the same access policy on the agent as on a human. The agent reasons over “net revenue (USD)” the metric, not a mystery column, and only ever sees data it is permitted to.
That makes AI answers reproducible, attributable, and safe to act on — the semantic layer becomes the agent’s source of truth.
Pre-launch scenario describing the AI-grounding capability being built.
Do it yourself
Point an AI agent at the governed semantic layer so it reasons over documented metrics with the same access policy as a human, and every answer resolves to an inspectable run.
Open the Agents page to manage the AI agents connected to your semantic layer.
You should see: The Agents page loads with your connected agents.
Ready to make this your story?
