/Logos/Atlas%20Fuse/Atlas%20Fuse%20website%20logo.svg "AtlasFuse, the trusted knowledge layer behind precise enterprise AI")
Apply ownership, permissions, sensitivity, approval status and lifecycle rules as knowledge is captured and managed.
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Connecting AI to enterprise data 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.
Microsoft 365 provides the core controls for permissions, retention, sensitivity labels, compliance and lifecycle management. AtlasFuse extends this by governing the knowledge layer: the business context, source-of-truth status, metadata, ownership, provenance and access rules that determine what people and AI systems can trust and use.
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.
AtlasFuse provides more extensive metadata such as knowledge type or source-of-truth status so that knowledge can be found, understood and reused in context.
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.
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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When AI is connected indiscriminately to large volumes of enterprise content, it can retrieve outdated drafts, superseded documents, sensitive information or knowledge that lacks clear ownership.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, rather than 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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