Apply ownership, permissions, sensitivity, approval status and lifecycle rules as knowledge is captured and managed.
Connecting AI to enterprise knowledge creates opportunity but it also creates risk. Not every document should be trusted, and not every user or AI experience should have access to everything.
AtlasFuse applies governance at the knowledge layer, helping firms control ownership, permissions, lifecycle, provenance and AI access before knowledge is activated.
So AI works from the right knowledge, for the right user, in the right context.
Apply ownership, permissions, sensitivity, approval status and lifecycle rules as knowledge is captured and managed.
Define which governed knowledge is available to Copilot, AI assistants, search, workflows and other AI experiences.
Respect existing permissions and apply additional knowledge controls so access remains appropriate to the user and use case.
Understand where knowledge came from, who owns it, how it has been managed and whether it can be trusted.
Giving AI more information doesn't automatically make it safer or better.
When AI is connected indiscriminately to large volumes of enterprise content, it can retrieve outdated drafts, superseded documents, sensitive information or knowledge that lacks clear ownership.
AtlasFuse governs the knowledge layer first, helping AI retrieve approved, relevant and appropriately accessible knowledge rather than simply retrieving everything it can find.
That makes governance part of the AI infrastructure should not be something teams have to recreate for every new AI initiative.
Respect existing permissions and define who can access specific knowledge collections.
Control which knowledge Copilot, AI assistants and workflows can access and use.
Review, refresh or retire knowledge according to business rules.
Understand where knowledge originated, who owns it and how it has been captured, structured or reused.
Maintain a clear record of what knowledge exists, how it is governed and where it is used.
Ground AI experiences in governed, approved and relevant knowledge.
Limit exposure to outdated, sensitive or inappropriate content.
Apply common controls across knowledge rather than rebuilding governance for each user and AI experience.
Give teams a safer foundation for expanding AI into knowledge-intensive workflows.
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