Risk Monitoring Dashboard-CX AI Designathon
How it all started
In today’s digital landscape, AI leads changes in industries by ensuring automation of processes, predicting outcomes, and providing actionable insights. The case is no different in the highly infrastructural domain of networking. For users of Cisco CX Cloud, AI is powerful and can enhance user experience through workflow smoothing, better decision-making, and reduced levels of downtime. Let’s dive into how this designathon generated wild ideas on leveraging AI for Cisco CX Cloud!
Reach out for Detailed Project
Timeline: 1 Week
My Role: Visual Design & Prototyping
I worked with 2 incredibly talented Lead Designers
Problem Domain
Large-scale network infrastructures are very vulnerable to software risks, system crashes, and compliance issues that result from an inefficient monitoring system.
Therefore, there is a need for a predictive risk monitoring tool that will analyze the risks involved and automate reporting with suggestions for proactive maintenance to reduce system vulnerabilities and operational inefficiencies.
How might we design a system for AI-powered risk monitoring that reduces risk vulnerabilities and operational inefficiencies within large-scale network infrastructures?
Not the usual Process
This Designathon required a shift in my usual process. Unlike previous projects with a well-defined flow, this one demanded a more iterative, agile approach. It called for quick thinking and rapid, continuous iteration to find the best solution in a short time. This non-linear design process, with constant back-and-forth, helped me navigate a complex problem domain using a fail-fast mindset.
Research Findings
As I embarked on this project, I turned to a wealth of research gathered from across Cisco’s ecosystem — insights from Cisco Live events, feedback from the CX Cloud Idea Exchange and reports from the Renewal Research team etc. Customers expressed a need for predictive analytics, smarter risk detection, and automated reporting. These voices became the foundational approach driving me to design a solution.
Leveraging AI
Some of the key questions that framed the approach as we set about developing the solution included: How would we ensure that AI actually predicts risks correctly without making any noise for the users? The ability to make such complex data available to all users, not just technical ones, was another huge challenge. Finally, how would confidence be instilled into AI?
Demo Showcase
We recently had the incredible opportunity to demo our project to senior leadership at Cisco including design architects and product owners, showcasing the value it brings to the company. It was a major achievement for me personally, being able to present a solution that aligns with Cisco’s vision.
Reach out for Detailed Project
Experience Counts!!
This designathon was not all about integrating AI, but a lot about collaboration, creativity, and teamwork. We had to rethink the design process with regard to AI so that we can make quicker and wiser decisions on an impending deadline. With this shift of incorporating AI, I was able to focus on key features without compromising on quality. Pressures of time bought quicker collaboration within the team, sparking rapid feedback loops driving fast iterations, and kept me on track without sacrificing innovation.
