<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>E-Commerce - Tag - TechBlog</title><link>https://techblog.unitymsp.it/tags/e-commerce/</link><description>E-Commerce - Tag - TechBlog</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Fri, 18 Sep 2026 10:05:20 +0200</lastBuildDate><atom:link href="https://techblog.unitymsp.it/tags/e-commerce/" rel="self" type="application/rss+xml"/><item><title>Univio CEB: Benchmarking AI for Enterprise and E-Commerce Workloads</title><link>https://techblog.unitymsp.it/posts/20260918-univio-ceb/</link><pubDate>Fri, 18 Sep 2026 10:05:20 +0200</pubDate><author>lbi</author><guid>https://techblog.unitymsp.it/posts/20260918-univio-ceb/</guid><description><![CDATA[<p>Choosing an AI model for business work is harder than comparing a few numbers on a public leaderboard. A model can perform well on general-purpose benchmarks and still struggle with the languages, data formats, tools, and long-running tasks used by an enterprise team every day.</p>
<p>This is why we built the <strong>Univio Commerce &amp; Enterprise Benchmark</strong>, or <strong>Univio CEB</strong>: a private evaluation environment for testing AI models, agents, and evaluation frameworks against practical enterprise and e-commerce scenarios.</p>]]></description></item></channel></rss>