<?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/b30ace685dcb485daeef9b7b609c4496&quot; frameborder=&quot;0&quot; width=&quot;1728&quot; height=&quot;1296&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1296</height><width>1728</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1296</thumbnail_height><thumbnail_width>1728</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/b30ace685dcb485daeef9b7b609c4496-c2e885237ac92bf8.gif</thumbnail_url><duration>315.147</duration><title>PawPawPlus Care Advisor Using RAG AI</title><description>Hi, I am Abel Tesfai, and this is my final project, PawPawPlus. It started as a pet scheduling app that plans tasks by time and priority, supports multiple pets, detects conflicts, and explains what gets skipped. I extended it with a RAG based AI Care Advisor that retrieves local device knowledge fast and works offline. After scheduling, it pulls care tips by pet species and age and shows a confidence level, like 29 percent for my dog. I also tested different inputs for consistency, and noted limitations around unverified data and only using existing information. No action was requested from viewers.</description></oembed>