Wazuh + UAIO: Autonomous SIEM That Closes the Loop

The Gap in Modern SIEM

Security teams today still operate in a reactive mode. A typical SIEM ingests terabytes of log data, correlates events, and raises alerts, but the path from alert to remediation remains manual and fragmented. According to the 2025 Ponemon Cost of a Data Breach report, the average dwell time before containment is 212 days, and 68 % of incidents are not fully mitigated within the first hour. Traditional workflows require separate ticketing, orchestration, and patching steps, each introducing latency and human error. The result is a SIEM that flags problems but does not close them.

UAIO’s Autonomous Loop

Unified Autonomous IT Operations (UAIO) changes that equation by embedding self‑healing directly into the detection pipeline. When Wazuh raises an alert, UAIO’s AI engine validates the event against a federated learning model, then initiates a predefined remediation workflow without human intervention. In a recent production deployment across 131 containers, the average time from detection to remediation was 20 seconds, reducing mean time to repair (MTTR) by 92 % compared to a manual process. This