Marvis Virtual Network Assistant
The Marvis Virtual Network Assistant (VNA) leverages Mist AI to transform how IT teams interact and engage with enterprise networks. With Natural Language Processing (NLP), a conversational interface, prescriptive actions, Self-Driving Network™ operations and integrated help desk functions, Marvis VNA streamlines operations and optimises user experiences from client-to-cloud – i.e. across wireless access, wired access, and SD-WAN domains.
Marvis is not just another “nice to have” tool. It is an essential member of your IT team, providing unsurpassed insight and automation. It is constantly learning as more data is ingested and using this ever-growing knowledge to proactively correct issues in real-time, predict problems before they occur, and/or solve trouble tickets as part of Juniper’s unique AI-driven support model.
- A conversational interface uses natural language to understand user intent.
- Marvis automatically takes action or provides recommendations to proactively fix an issue before users know it exists.
- Marvis Android app enables a client-level view of the network, capturing events directly from end-users’ devices.
- Validated Mist AI-driven support can decrease user-generated tickets by up to 90 percent.
- Real-time insights and simplified troubleshooting at the client, device, and site levels help boost service quality.
Features and benefits
The Marvis Conversational Interface uses advanced natural language processing (NLP) to understand user intent and goals. It contextualises 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 prioritise 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.