What if you could chat with your wireless network?
Meet Marvis – the first AI-driven assistant. Now you can ask questions and get intuitive answers on par with a wireless expert.
Maximize User Experience
- Faster troubleshooting means less downtime
- Proactively fix problems before users know they exist
Prioritize IT Spend
- Focus IT investments on strategic projects not on troubleshooting
- Prioritize helpdesk tickets based on scope of impact
Gain New Insights
- Understand your WLAN without hunting through numerous screens
- Analyze and correlate date to determine the magnitude and scope of problems
Key Components of Marvis
Marvis adds anomaly detection to the Mist SLE dashboard so that administrators can rapidly and proactively identify service impacting events that assure rapid determination and resolution of the root cause of issues. Anomaly detection leverages data science tools to automatically determine service baselines and trigger notifications when there is a service-impacting deviation from that baseline. With our API driven interface, detected anomalies can even trigger external events such as creation of a help desk ticket, without manual intervention.
Correlate Data to Understand Scope
Marvis correlates information across a large knowledge base to determine the scope and magnitude of a problem. This helps you prioritize issues and assign resources efficiently.
- Did an upgrade cause a wireless issue?
- Is it specific to client, group of clients, entire site, or many locations?
- Is it happening rarely, occasionally, or frequently?
- Is there a coverage issue or is a DHCP server responding slowly?
- What is the scope and impact of the problem?
Integrated Help Desk
Marvis uses machine learning to perform unique troubleshooting and helpdesk functions like anomaly detection, event correlation, and confidence ratings. By leveraging APIs, this can trigger automated workflows so you can rapidly solve (or avoid) wired, wireless and device problems.