Qevlar AI Autonomous SOC Platform

What it does

The Qevlar AI Autonomous SOC Platform investigates security operations center (SOC) alerts end to end, from trigger to verdict, with no playbooks and no analyst starting the process. A deterministic graph orchestrator performs the investigative reasoning on the same path every time, while large language model (LLM) agents handle only bounded enrichment and reporting tasks. Each alert closes with a Malicious, Suspicious, Benign or Missing Data verdict, related alerts are correlated into incidents, and every outcome feeds detection tuning, threat hunting and vulnerability prioritization.

How it works

When an alert fires, the graph orchestrator extracts observables, enriches them through threat intelligence and Qevlar Eye, which renders pages and scans attachments, and pivots across logs to reach a verdict. Each report documents every step and ends with up to five next steps, including Microsoft Entra ID containment actions analysts run from the report. Admin-approved Organizational Context items steer future investigations, and Identity Hunt builds a baseline from roughly 30 days of authentication logs for any user involved. Teams use the console or run headless with reports pushed to ticketing, and customers include Sodexo, GlobalConnect, Nomios and Almond.

Credentials and traction

Qevlar AI is SOC 2 Type II certified and is featured in the AI SOC Agents category of the Gartner Hype Cycle for Security Operations, 2026. It won the 2025 MSP Today Product of the Year award and the 2026 InCyber Forum Europe Growth Award, and CB Insights ranked it first for Mosaic score improvement in the 2025 SOC AI market. The platform is in production at 1,500 organizations, with customers including Mercedes-Benz, Sodexo, Orange Cyberdefense, Atos and ECI.