video1.0<iframe src="https://www.loom.com/embed/cba9b665b5ca49979a89bfda5fbcd362" frameborder="0" width="1662" height="1246" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12461662Loomhttps://www.loom.com12461662https://cdn.loom.com/sessions/thumbnails/cba9b665b5ca49979a89bfda5fbcd362-2b9bc3a22235627a.gif713.269In this video, I present my second iteration of the Service Call Manager, developed for the Gauntlet AI Cohort 2 project. This application aims to streamline our service call management process, which is currently disorganized and paper-based, by allowing us to easily track and manage service calls for major residential appliances. Key features include a dashboard for monitoring service calls, an AI-driven parts analysis to reduce repeat visits, and a stale calls alert system to ensure timely follow-ups. I also attempted to integrate customer texting for confirmations and reviews, but faced some challenges. I encourage you to provide any feedback or suggestions on the application as we continue to refine it.