AIRMDR vs Qevlar AI
A detailed side-by-side comparison to help you choose the right AI cybersecurity agent for your needs.
Best for fully managed AI-powered MDR and SOC automation
AIRMDR
AIRMDR delivers a fully managed detection and response service where AI agents handle the heavy lifting of SOC operations around the clock. The platform ingests telemetry from endpoints, networks, clo...
AI Models
Proprietary threat intelligence MLCustom NLP for log analysisBehavioral anomaly models
Key Features
- 24/7 autonomous alert triage and threat investigation
- Automated containment: endpoint isolation, account disable, IP block
- Behavioral baseline analysis across users, devices, and apps
- Threat intelligence correlation across global IOC feeds
- Automated incident narrative generation for analyst review
Pricing
Starter MDR — Custom pricing
Business MDR — Custom pricing
Enterprise MDR — Custom pricing
Pros
- Fully managed service eliminates the need to hire in-house SOC analysts
- Autonomous containment actions dramatically cut mean time to respond
- Behavioral analysis catches sophisticated threats that bypass signature rules
Cons
- Custom pricing with no public tiers requires a sales conversation to evaluate cost
- Managed service model means less direct control over investigation decisions
Best for AI-powered autonomous security investigations
Qevlar AI
Qevlar AI is built around one central premise: security investigations take too long because they require analysts to manually pivot across dozens of tools, correlate disparate data sources, and const...
AI Models
GPT-4oProprietary graph reasoning modelsCustom ML for IOC correlation
Key Features
- Autonomous multi-hop investigation across identity, network, and endpoint
- Attack timeline reconstruction from initial alert to full scope
- Lateral movement and privilege escalation detection across data sources
- Structured investigation reports with prioritized remediation steps
- Institutional memory of past investigations for pattern recognition
Pricing
Growth — Custom pricing
Enterprise — Custom pricing
Pros
- Autonomous multi-source pivoting eliminates manual investigation steps
- Institutional memory improves accuracy for recurring threat patterns
- Preserves existing tooling investment by acting as an intelligence layer
Cons
- Investigation quality depends heavily on data availability in connected sources
- Pricing not publicly listed, requiring sales engagement for evaluation