Rahsi SharePoint Memory Spine™ | Governing Copilot at Tenant Scale

#sharepoint #ai #governance #githubcopilot

Most organizations are losing the AI governance battle without realizing it.

While everyone races to deploy Copilot, they're missing what happens underneath:

Unstructured data flowing into inference surfaces with zero memory governance
Semantic drift accelerating unchecked
Tenant-scale exposure growing exponentially

Introducing the Rahsi SharePoint Memory Spine™

I've spent the last few months building something different.

Not another checklist.

Not another framework deck.

An actual implementation spine.

Rahsi SharePoint Memory Spine™

A technical architecture that governs Copilot at tenant scale by treating SharePoint not as storage —

but as the memory governance layer Microsoft 365 was always missing.

The Approach

Content Planes partition inference exposure
Metadata Truth Anchors prevent semantic drift
SPFx Application Customizers create behavioral labels at the interaction layer
Power Automate orchestrates flow provenance
Purview becomes enforceable, not aspirational

The Stack

No consultants.

No six-month roadmaps.

Just:

SPFx
TypeScript
Microsoft Graph
Substrate APIs

This isn’t theory. It’s production.

And it’s working.

Telemetry Signals Emerging

AI memory decay rates dropping
Inference accuracy climbing
Security teams finally sleeping

Why It Works

Microsoft built the AI
SharePoint holds the memory
SPFx controls the interaction surface

The Spine connects all three.

If You’re Governing Copilot with Policies Alone

You're already behind.

The game changed the moment AI started reading your unstructured data.

Memory governance isn't optional anymore.

Happy to share the full architecture with anyone building in this space.

The Azure ecosystem wins when we solve hard problems together — quietly, with working code.