<?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/098b01fc0b19475e9d9ee7551c17173b&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/098b01fc0b19475e9d9ee7551c17173b-27a40c1040ec2ee4.gif</thumbnail_url><duration>91.915</duration><title>Knowledge Search Use Case</title><description>In this video, I demonstrate how Convictional integrates with various data and knowledge sources to enable a comprehensive contextual search within our company. By connecting to platforms like GitHub, Google Drive, and our company website, Convictional allows me to ask specific questions and retrieve relevant information efficiently. I showcase how I utilized this feature to understand a new release before the holiday break, highlighting its ability to provide detailed summaries and linked context for better communication with customers.</description></oembed>