video1.0<iframe src="https://www.loom.com/embed/aea10780b01f4071affb1275ba223c9c" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/aea10780b01f4071affb1275ba223c9c-63ce94524ebb8858.gif298.0025Hi everyone, this is Aditya Coomar, and in this video, I present my second assignment for Attack Capital, which is a smart outbound call detection system. The system utilizes multiple AMD strategies, including Twilio's native AMD, Jamboz, a Hugging Face model, and Gemini testing. I demonstrate the functionality by testing two AMD strategies, showcasing how the system effectively detects whether a call is answered by a human or a machine, such as a voicemail. The tech stack includes Next.js, Tailwind CSS, and FastAPI for the Hugging Face model. I encourage you to review the demo and provide feedback on the current dashboard and features.