<?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/82e828a2431c4e87af55e88623fb8167&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/82e828a2431c4e87af55e88623fb8167-b10425a3a2ead9b6.gif</thumbnail_url><duration>369.813</duration><title>Continuous GRC Intelligence With Trust Signals 🌐</title><description>In this Loom, I share a blue ocean use case for Crux Data API with agent driven MCPs in GRC, specifically TPRM or Risk Intelligence Scan. I explain how GRC teams run quarterly cycles on manual spreadsheets, so by the time risks are flagged, it is already a problem. We built a continuous intelligence layer between real world signals and your GRC system to continuously validate what is true. I show a demo triggered by a TrustDataAPI webhook where an AI agent pulls external signals like funding rounds and headcount changes to surface operational and financial risk. No action was explicitly requested from viewers.</description></oembed>