Rahsi™ AI SOC Interface Layer | Where Assistance Becomes Accountable

🧩 Rahsi™ AI SOC Interface Layer

Where Assistance Becomes Accountable

Not a chatbot. Not a UI.

A runtime control plane that forces every AI action to be provable:

• 🛡️Who asked
• 🛡️What data it touched (and what it didn’t)
• 🛡️Under which session risk (Entra + Conditional Access + device posture)
• 🛡️ Which controls enforced (Purview labels, DLP, Defender policies)
• 🛡️What evidence got stamped into Sentinel for audit + post-incident truth

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This is the missing interface between:

Defender XDR + Sentinel + Entra + Purview + Copilot/agentic tooling

It’s the layer that prevents “helpful” from becoming “harmful” — during:

• CVE surge windows
• Insider-risk escalations
• High-pressure containment calls

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🔍 If Your SOC Can’t Reconstruct It, It Shouldn’t Happen

If your SOC can’t reconstruct why the AI said something and what it had access to at that moment…

You don’t have automation.

You have liability.

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🛡️ Read Complete Article | https://www.aakashrahsi.online/post/rahsi-ai-soc

I’m publishing the full architecture:

• Control points
• Evidence-pack design
• Enforcement logic

That turns “AI in the SOC” into something compliance and leadership can actually sign off on.

Because “copilot” without control is exposure.

And automation without audit is breach-by-design.

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Let’s rebuild the SOC | not with more dashboards, but with proof.