It applies AI to the judgment layer of patching, not just execution. Instead of running static rules, agents prioritize dynamically, orchestrate deployments based on real device usage, self-monitor and self-correct mid-rollout, and document everything — so patching runs continuously without manual babysitting.

Agents correlate exploit probability, active-exploitation status, and each asset’s exposure to decide what genuinely matters in your environment, then choose ring progressions and windows based on observed usage patterns. You set the risk tolerance — how much exploit probability justifies bypassing a maintenance window — and the agents operate within it.

Yes. Patches move through pilot, validation, and production rings with progression based on actual results, inside maintenance windows, with rollback protection built in. Agents detect elevated failure rates mid-rollout, halt automatically, and roll back — without waiting for a human to notice.

Yes — and that matters, because third-party software like Chrome, Java, and .NET is where most breaches begin and where manual remediation drags on the longest. It patches thousands of third-party applications alongside Windows, Linux, and macOS.

Yes. It scans and patches across on-premises and AWS, Azure, GCP, and OCI from one control plane — so coverage is consistent no matter where a system runs.

Continuous enforcement keeps you inside remediation windows — including the 7–21 day timelines expected for actively-exploited vulnerabilities — and maps to frameworks like NIST SP 800-53, PCI DSS, and HIPAA, generating the compliance evidence trail automatically and feeding it into Smart Audit.