AI SOC
MSSP
Multi-Tenant SOC
Decision Layer
Multi-Tenant AI SOC: Why Autonomy Isn't Enough for MSSPs
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Lead Solutions Architect at Arcanna
He started his career building SOC operations at an MSSP, setting up tooling, writing detections, and running investigations, before joining Arcanna to help customers deploy AI decision models and agentic workflows in production. He is the main user of the platform Arcanna is building.
Practitioner interviews
INSIDE ARCANNA
3 perspectives on why existing security stacks are breaking, and what trustworthy AI in operations actually requires.
Darius Iakabos
Lead Solutions Architect
“SOAR was built for predictable workflows. SOC reality isn’t predictable.”
Why SOAR’s scaling ceiling isn’t compute — it’s the playbook maintenance burden — and what replaces it.
27 MINWatch
Alina Marcu, PhD
Chief Data Scientist
“AI without governance isn’t intelligence. It’s exposure.”
What a Trust Layer actually does — and why grounded decisions, drift control, and rollback are the price of putting AI in front of operations.
23 MINWatch
Denis Stefan
AI Engineer
“An agentic investigation works when the agent knows what it doesn’t know.”
How agentic investigations actually run end-to-end — structured outputs, decision-model guardrails, and verification at every step.
18 MINWatch
Keep Reading
Why SOAR Breaks at Scale, and What Actually Replaces It
The ceiling isn't compute, it's the headcount to maintain static automation.
ReadGoverning AI in the SOC: The Case for a Trust Layer
Why grounded decisions, drift control, and rollback are the price of AI in operations.
ReadWhat to Look for in AI SOC Platforms: Thresholds, Drift, and Control
The criteria that separate a trustworthy AI SOC from a confident guess.
ReadPredictable Alert Triage at Scale: Why SOC Consistency Beats Raw Automation
Consistency, not raw speed, is what survives an audit.
ReadWhat Are Decision Models?
The deterministic, per-tenant layer that grounds verdicts in your team's judgment.
Read