There’s an increasingly strong correlation between high-capacity, high-reliability wireless networks and a customer experience that inspires long-term loyalty. However, building durable and scalable networks often proves challenging due to the number of devices, applications and sensors relying on it to function anytime, anywhere. Mist, a Juniper company, offers a creative new way of approaching some of these challenges that goes beyond just keeping access points online.
The value of an AI-Driven Network
Mist access point network infrastructure platform is designed to automate monitoring, reporting and troubleshooting of the network with minimal input from the business. Built on a cloud-based microservices architecture and powered by machine learning, Mist adapts and optimises wireless networks for performance in real time, ensuring businesses can deliver strong connectivity to customers and employees even when usage patterns shift rapidly.
To help keep networks optimised, Mist can:
- Automatically track and switch users to clear wireless bands, based on performance thresholds that the business can “set and forget”
- Answer IT’s questions and provide swift recommendations thanks to Marvis, the platform’s inbuilt AI engine that comes with Natural Language Processing (NLP) and data analytics
- Rapidly capture and analyses over a hundred user states at any given time, giving network admins critical metadata to solve more complex problems from a single dashboard
- Adapt to constantly evolving business and end-user needs with microservice-based cloud architecture and open APIs
To me, what stands out about Mist is that adaptability – not only accommodating rapid changes in user behaviour, but also using features like Marvis to empower IT teams as they strive to solve issues in a fast and agile fashion. Marvis proactively surfaces potential issues to net admins’ consoles – like picking up missing VLANs on specific access points – before user complaints highlight an issue, which could prove a potential game-changer for how many businesses govern their infrastructure. This goes a step beyond automation or uptime capabilities that many other solutions provide, acknowledging that what defines a best-in-class user experience can shift as quickly and often unpredictably as the weather.
Supporting wireless networks from within
Our customers using Mist tend to also comment on the solution’s ability to deliver a consistent experience, especially in BYOD-centric environments like campuses, office buildings and co-working spaces. For such customers, the constant inflows of new devices and applications means users are often assigned to sub-optimal wireless network frequencies, ultimately resulting in slow connectivity. Mist tackles this issue by using machine learning to guide its Radio Resource Management (RRM) algorithms, which results in less coverage and capacity shortfalls. Coppell Independent School District, for example, is spending less time chasing down inconsistencies in the wireless network or puzzling out connectivity issues with Mist – allowing the school to focus on improving students’ learning paths and supporting its teaching staff with the connectivity that Mist provides.
We’re also starting to use Mist to tackle IoT and application-heavy ecosystems to great effect. It can be nearly impossible to manually track the sheer volume of data through these networks, particularly at a rate required for operations to remain stable and efficient. By tapping into Mist’s machine learning algorithms, we’re seeing enterprises significantly reduce how long it takes for them to pinpoint and resolve issues.
User experience is no longer determined by uptime alone
If you’re considering Mist as a solution for your customers’ network infrastructure, remember that user experience is no longer determined by uptime alone. Rather, it’s the network’s ability to generate solid business outcomes – like an innovative and reliable customer experience, keeping productivity levels high or resilient yet low-maintenance cyber risk mitigation – that matters most. Mist’s responsiveness and adaptability directly contribute to those outcomes, and we’re particularly impressed by how Marvis bolsters IT’s problem-solving abilities while employing Mist’s substantial machine-learning smarts to deal with less visible issues automatically.
Mist “brings the rain” for businesses that want to rapidly ramp up their customer experience game and elevate IT from everyday maintenance to generating business ROI with data-driven insights. Large retailers and banks in Australia have taken the leap forward with Mist’s self-driving network. If you’d like to learn more about how Mist can help your customers grow and optimise their network infrastructure, get in touch with us today.