Qevlar AI

Categories: Cybersecurity, Automation / Agents, Data Analysis | Pricing: Enterprise | Official Website ↗

Qevlar AI is an autonomous SOC platform that transforms daily security operations into a self-improving defense system.

Qevlar AI provides an autonomous Security Operations Center (SOC) platform designed to enhance an organization's defense capabilities. It addresses the common problem of security teams being overwhelmed by alerts and operating in silos, leading to knowledge loss and inefficient defense. The platform aims to close the loop on security incidents, making defenses stronger with each action taken. The system investigates and responds to alerts across an organization's entire security stack, connecting related activities into single incident stories, mapping blast radii, and moving containment forward according to established procedures. It continuously hunts for emerging threats, attacker TTPs, behavioral anomalies, and active exploitation, turning every finding into action and every gap into an opportunity to strengthen detection. Qevlar AI also compounds institutional knowledge, adapting to the environment to make investigations faster and decisions more consistent, and connects SOC and vulnerability teams through a shared intelligence layer for prioritizing real risks.

Key Features

Autonomous investigation and response across security stack
Continuous threat hunting
Incident correlation and blast radius mapping
Automated containment and tuning
Institutional knowledge compounding
Shared intelligence layer for SOC and vulnerability teams
Transparent verdict reasoning
Integration with existing security tools via API

Pros

Transforms daily SOC activity into a self-improving defense system
Closes the loop on incidents, making defenses stronger with each action
Investigates and responds across the entire security stack
Continuously hunts for emerging threats and behavioral anomalies
Compounds institutional knowledge, making the SOC smarter over time
Provides full transparency into every verdict and reasoning

Cons

Pricing information is not publicly disclosed
Requires integration with existing security infrastructure
Specific implementation details for different environments are not detailed
Relies on analyst trust in AI verdicts, though transparency is provided

Use Cases

Automating security investigations and responses
Enhancing threat hunting capabilities
Prioritizing vulnerabilities based on confirmed exploitation
Improving consistency of security operations and policy execution
Increasing SOC capacity without additional headcount

Best For

Enterprises with large security operations centers
Managed Security Service Providers (MSSPs)
Organizations seeking to improve incident response efficiency
Security teams struggling with alert fatigue and siloed operations

Integrations: Atos cybersecurity, Almond CWATCH SOC (SOAR, SIEM, XDR, ITERA, M&NTIS), Sopra Steria MDR

Platforms: Web

Watch demo on YouTube ↗

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