45,000+
CVEs disclosed annually
Your Patch Programme is Under Attack
AI has permanently transformed vulnerability discovery from an expert-driven process into an industrialised capability operating at machine speed. Ivanti Neurons for Patch Management uses Autonomous Endpoint Management to close the gap between vulnerability discovery and remediation—automatically prioritising, deploying, and verifying patches at machine speed.

These numbers reflect today's reality—and AI is accelerating the pace.
CVEs disclosed annually
Average time-to-exploit
year-over-year rise in AI-enabled attacks
Autonomous Endpoint Management (AEM) that detects vulnerabilities, decides what to patch, and acts—all at machine speed.
Continuous Compliance: Zero-Touch Patch Remediation
Ivanti Neurons doesn't just find vulnerabilities—it automatically remediates them based on your risk appetite. When assets drift out of compliance or miss scheduled deployments, AEM-powered remediation occurs automatically, maintaining continuous compliance without human intervention.
Self-protecting endpoints that discover threats, assess risk, and remediate vulnerabilities automatically. Your devices become autonomous agents that patch themselves based on your defined risk policies.
Integration with vulnerability intelligence automatically escalates business critical CVEs. When a vulnerability moves from disclosed to actively exploited, Ivanti Neurons prioritises it immediately—no human reclassification needed.
Patch without disruption. DEX monitors endpoint health and user activity, scheduling updates during low-impact windows. User sentiment surveys continuously measure device health and experience, identifying performance issues before they impact productivity. This proactive approach keeps endpoints secure and employees happy.
Discover and manage every endpoint—including shadow IT, cloud workloads, mobile devices, and offline assets. Real-time inventory ensures you can patch every vulnerable device, not just the ones you know about.
Automated compliance verification confirms actual patch installation and configuration state. Continuous compliance evidence is generated automatically as patches deploy—no more fire drills before audits.
Test ring, early-adopter ring, broad production, mission-critical. The sequence is automated and instrumented. If an update causes issues, automatic rollback protects operations while you investigate.
Features and capabilities
Everything you need to match machine-speed vulnerability discovery with machine-speed remediation.
Schedule updates to minimise disruptions and maintain workforce productivity.
Roll out updates in controlled rings and capture user sentiment to iterate on deployment strategies.
Get ahead of downstream issues with device hygiene checks and actionable fix suggestions powered by AI.
Tie risk-aligned patch decisions and experience outcomes back into ITSM and RBVM workflows.
Automate remediation of common device and application issues, improving rollout success by preventing failures like insufficient disc space.
Leverage vulnerability intelligence to focus on the most business-critical patches first, reducing exposure to threats.
Continuously measure digital experience scores and correlate them with patching activities.
Simplify audits with automated reports for patch compliance and experience improvements.
Keep BIOS, drivers and firmware current, even when maintenance windows are constrained.
The patch apocalypse refers to the rapid increase in publicly disclosed vulnerabilities with available patches, driven by AI‑accelerated vulnerability discovery. The volume and speed of fixes are beginning to outpace how most IT and security teams can reasonably remediate them using traditional, human‑driven workflows.
An autonomous endpoint management (AEM) platform, with ring-based deployment and rollback, and vulnerability intelligence can provide risk-based context for efficient remediation decisions.
By adopting a risk-based patch management approach, it incorporates real-world threat context to focus on vulnerabilities that are actively being exploited. The approach goes beyond traditional vendor severity ratings and CVSS scores to identify and prioritise vulnerabilities based on their actual risk to an organisation.
AI models can identify vulnerabilities at a scale and speed humans cannot match. As attackers gain access to similar AI model capabilities, they will target newly disclosed vulnerabilities faster. Organisations relying on manual, fragmented patching processes will see increasing exposure – not because patches don’t exist, but because they can’t deploy them fast enough.
No. Vulnerability scanners are essential for discovery, but they don’t deploy patches, verify instals, manage rollbacks, or close the loop. At high CVE volumes, scanners that generate long critical lists without automation behind them can actually slow remediation.
Linear approval workflows were designed for slower patch cycles and don’t address today’s realities. When teams already know updates will be deployed, additional approvals add delay without reducing risk. In a fast-moving threat environment, time is often the limiting factor.
See how Ivanti Neurons for Patch Management can transform your vulnerability management programme from reactive to autonomous.