Proactive Issue Resolution with Healing Bots
This demonstration showcases Ivanti Neurons' approach to pre-ticket automation, where AI-powered healing bots continuously monitor endpoints to detect and resolve issues before users even notice them. The session explains how these bots address a critical gap in traditional service desk operations — the estimated 50% of incidents that users never report because they simply tolerate poor performance. By deploying healing bots that proactively scan for problems like application errors, blue screens, and performance degradation, IT teams can fix issues before they escalate into formal tickets. When automated remediation isn't possible, the bots log high-context tickets directly to the service desk with diagnostic information already attached, eliminating the need for time-consuming initial triage.
Post-Ticket Automation and First-Call Resolution
The session demonstrates how Ivanti Neurons enables service desk analysts to leverage healing bots for post-ticket automation, dramatically improving first-call resolution rates. Rather than escalating tickets to second and third-line support or interrupting end users with remote control sessions, analysts can execute diagnostic and remediation bots directly from the ticketing interface. This approach operationalizes existing knowledge — converting work instructions, scripts, and knowledge articles into automated actions that run in real-time against affected devices. The demonstration shows how analysts can pull comprehensive device diagnostics, query real-time performance data across the entire fleet using Edge Intelligence, and drill down from fleet-wide trends to specific login script bottlenecks causing performance issues.
Incident Correlation for Major Issue Detection
A key capability highlighted is Ivanti's incident correlation engine, which analyzes incoming tickets from multiple sources — bot-generated incidents, user-submitted requests, third-party event management systems — to identify patterns indicating widespread problems. The demonstration shows how the system automatically clusters similar incidents (in this case, 21 reports of slow logon performance) and visualizes trends with color-coded indicators showing whether incident rates are increasing or decreasing. Service desk managers can then assign a parent ticket to the cluster, linking all related child tickets to streamline investigation and ensure consistent communication. This transforms reactive ticket handling into proactive problem management, enabling teams to identify and address systemic issues like a faulty logon script deployment before they impact the broader user base.
