<?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/7fb37c1f816e42fea4394933f1ddc2a3&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/7fb37c1f816e42fea4394933f1ddc2a3-41501fa32200a5b9.gif</thumbnail_url><duration>231.213</duration><title>Acipta.ai Evidence and Compliance for AI</title><description>This Loom explains how Acipta.ai provides cryptographically signed, byte-identical replayable AI compliance verdicts for enterprises deploying LLMs at scale. It contrasts two CSA operating documents: securing LLM backend systems and managing AI model risk, noting the common gap where teams cannot produce defensible evidence fast enough. Asipta uses three frontier models (claims include GPT-5, Gemini, and a Cloud model) with a 0.85 confidence floor and a consensus rule requiring at least two-thirds agreement; if not, it routes to a human in the loop. Each verdict is signed at write-on, timestamped using RFC 31618, and replayable for five years, with GA expected on August 23.</description></oembed>