Interactive Demo
Designing for Cisco's AI capabilities
Project Overview & Goal
• Role: Interaction Designer for Demo Video
• Company: Cisco
• Tools: Figma, Walnut.io, Click Up
• Timeline: 1 month
I designed an interactive prototype showcasing Cisco’s AI capabilities in assisting TAC with troubleshooting technical issues. The demo highlighted Cisco’s ability to deliver real-world solutions, aiming to enhance customer understanding and improve conversion rates. The project’s primary goal was to create this prototype and embed it into Walnut.io, an interactive demo platform, to provide a comprehensive and engaging product experience.
Problem Statement
A key challenge in this project was the confidential nature of the TAC interface, requiring me to design a prototype that closely resembled the actual system without revealing sensitive details. Additionally, the project faced tight timelines and evolving requirements, adding complexity to the design process.
Research & Ideation
As AI tools rapidly gain traction, it became essential to conduct thorough research before presenting this prototype to a broader audience at Cisco events. I collaborated closely with TAC engineers to understand how AI could quickly transcribe and analyze issues once a case was submitted into the system.
Cisco’s Gen AI enhances the customer experience by accelerating response times, generating an initial solution based on the customer’s query, and then having a real TAC engineer review the response before final submission.
Prototyping
To create an engaging interactive prototype, I aimed to develop an interface that closely resembled the real TAC system while safeguarding confidential information. After reviewing the TAC engineers’ screens and examining sample email issues and their solutions, I started designing the prototype in Figma. The challenge was balancing realism and security, ensuring the interface felt authentic without revealing sensitive details. Once the design was finalized, I integrated the prototype into Walnut.io, where users could interact with it seamlessly, offering a near-real experience of the AI-driven solution.
Learning & Takeaways
This project taught me the value of embracing progress over perfection, especially when working with ambiguous requirements, tight timelines, and coordinating with offshore teams. I learned the importance of seeking feedback early and often, which allowed me to adapt quickly and make improvements throughout the process. Clear communication and flexibility became crucial as the project evolved. Ultimately, it reinforced the idea that iteration and collaboration are key to delivering a successful solution under challenging conditions.