<?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/fd7af0c5083e478ebb8da5c8e2b03f05&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/fd7af0c5083e478ebb8da5c8e2b03f05-a4c7480d4b20821d.gif</thumbnail_url><duration>300.725</duration><title>Streamlining Data Analysis and Reporting with AI Solutions</title><description>In this video, I discuss my work on the AFR, LDR, Project Pipeline, focusing on the challenges of manual inspections and report generation. I&apos;ve developed a web application that automates data analysis, generating detailed reports with color-coded diagnostics in a 50-page format. I also highlight the need for improvements, such as implementing OCR for linking images to text and creating a dynamic dashboard for better updates. My current process takes about two to three minutes to generate a report, and I aim to enhance efficiency further. I welcome any feedback or suggestions on these initiatives.</description></oembed>