<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/7d130500e8a04b4f8535ea0015e92389&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/7d130500e8a04b4f8535ea0015e92389-fc7e6e2d600eff5e.gif</thumbnail_url><duration>33.418</duration><title>Automating Client Responses with Text Classification 🤖</title><description>In this video, I walk you through my workflow for processing email replies that come in through a webhook. I explain how I match these replies to the corresponding clients and utilize a text classifier to analyze the content. The classifier has provided some interesting outputs that I want to discuss further. Please take a look at the results and let me know your thoughts on how we can improve this process. Your feedback will be invaluable as we refine our approach.</description></oembed>