Overview
Tens of thousands of new vulnerabilities are published every year, and only a small fraction are ever exploited. Prioritising by CVSS score alone sends teams chasing the wrong issues while truly dangerous ones wait.
Our AI-driven vulnerability management combines scanner data with exploit intelligence (such as EPSS and known-exploited vulnerability catalogues), asset criticality, internet exposure and compensating controls. Machine-learning models deduplicate findings across tools and rank them by real-world risk, while analysts validate the top priorities.
AI also helps generate clear, environment-specific remediation guidance for owners — speeding up fixes without overwhelming them.
What's included
Our approach
- IntegrateConnect existing scanners and asset sources.
- ModelConfigure risk scoring with your context.
- PrioritiseRank vulnerabilities by predicted risk.
- RemediateRoute fixes to owners with clear guidance.
- MeasureReport risk reduction and SLA performance.
What you receive
- Unified vulnerability view
- Risk-ranked remediation queue
- Owner-specific fix guidance
- SLA and risk-trend dashboards
- Monthly executive summary
Standards & frameworks
- CVSS v4.0
- EPSS
- CISA KEV catalogue
- ISO/IEC 27001 A.8.8
- NIST SP 800-40
Frequently asked questions
How is this different from traditional vulnerability management?
Instead of sorting by severity alone, we predict which vulnerabilities are likely to be exploited in your environment and prioritise those.
Do we need new scanners?
Usually not. We aggregate data from the tools you already use.
Is human review still involved?
Yes. Analysts validate the highest-priority findings before they are escalated.