<?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/0dceb75dd433455d9ee721036887476d&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/0dceb75dd433455d9ee721036887476d-cb3591a5fab7a428.gif</thumbnail_url><duration>94.379</duration><title>Enhancing AI Match Scores with Video Screening Insights</title><description>In this video, I’m providing an update on our AI score matching feature that we launched last month, which has received positive feedback from initial users. We identified a gap in the process where candidates&apos; video screenings could influence their AI match scores, so we’ve implemented a new system to record and transcribe these videos. This allows us to extract additional data and rerun the AI match, often resulting in an updated score. I encourage everyone to familiarize themselves with this enhancement as it can significantly improve our candidate evaluation process.</description></oembed>