The Marvis Conversational Interface uses advanced natural language processing (NLP) to understand user intent and goals. It contextualizes the inquiry to return specific results and can even take actions based on user feedback. Describe your intent to Marvis, and it will take an action without requiring you to remember specific dashboards or CLI commands to implement the change.

Currently for Android only. Get network visibility inside out, from the device’s perspective. In addition to the rich visibility of the device’s Wi-Fi experience, you can now understand how the device sees the Wi-Fi environment.

Marvis adds anomaly detection within service-level expectation (SLEs) so you can proactively identify service-impacting events and determine the root cause for rapid remediation and resolution.

Marvis uses Bayesian Inference to identify causes with the highest probability of association to problems occurring on the network. This approach delivers more accurate root cause analysis to speed problem identification and resolution.

Marvis correlates information across a large knowledge base, including WLAN, LAN, WAN, and security domains, to determine the scope and magnitude of a problem. This correlation helps you to prioritize issues, allocate resources efficiently, and reduce pressure on support teams.

Marvis Actions, a function of the Self-Driving Network™, leverages Mist AI to identify the root cause of issues across IT domains (WLAN, LAN, WAN, and security). It automatically fixes or recommends actions (driver-assist mode) with high efficacy for connected systems outside of the Juniper domain.