Case Study · AI SOC · In Progress

AI SOC Pilot

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The brief

This client wanted the benefits of an AI-driven SOC — faster detection, automated triage, fewer noisy alerts — without committing to expensive commercial platforms before proving the approach works for their environment. MeyLing proposed an open-source-first pilot.

What we did

We're deploying Wazuh and OpenSearch for log correlation and detection, with TheHive and Shuffle SOAR layered on for case management and triage automation. Every component is open-source by default; commercial tooling stays on the table only if the pilot's results justify the spend.

How we ran the engagement

The pilot runs alongside the client's existing monitoring rather than replacing it outright, so nothing is at risk while we tune detection rules and automation playbooks against their real traffic patterns.

Client

Pilot engagement — in progress

Scope

Open-source AI SOC: detection, triage, alerting

Delivery window

Active pilot, phased rollout

Status

Phase 1 (detection & log correlation) in active deployment since Q3 2025. This page will be updated with results once Phase 1 completes.

Outcomes

Open-source-first, budget-neutral start Automated alert triage in testing Results reviewed before any paid tooling

Exploring an AI SOC for your environment?

We'll scope an open-source-first pilot against your real traffic, with paid tooling only where the results justify it.