Per-tenant normals
Not one model for the whole stack.
A managed security provider used mysoc.ai to automate tier-1 triage, investigation, and customer communication across tenants — so growth stopped waiting on hiring.
“We onboarded 12 new customers last quarter without adding headcount. The AI handles triage and customer reporting—our analysts only see real threats.”
This MSSP’s growth was capped by the same constraint every managed SOC hits: every new customer means more alerts, more chat, more monthly reports — and another body on the tier-1 rotation.
What was breaking:
Bolt-on AI on a shared queue fails in multi-tenant life: each customer’s baseline is different. What looks anomalous for Tenant A is Tuesday afternoon for Tenant B.
They needed:
Not one model for the whole stack.
Triage → investigate → tell the customer → report.
Not a rip-and-replace.
They deployed mysoc.ai as the AI SOC operations layer — alongside their existing SIEM, not instead of it.
New customer environments onboarded in under a day; existing firewalls, EDRs, and SIEM stayed.
SiemCore built a Sphere of Normalcy per tenant — noise dropped before humans touched the queue.
AI tier-1 enriched and escalated; humans focused on verified threats.
Notifications, chat, and reporting handled in-product per customer.
Closed investigations tuned that tenant’s baselines.
We publish only the numbers already on the public record for this anonymized customer.
Growth decoupled from hiring. Margin looked more like software. Customers still got a SOC that answered them — triage and reporting handled in-product, so analysts only saw real threats.
See how mysoc.ai runs tier-1 for multi-tenant SOCs — cloud or on-prem.