<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>ScrapeGraphAI on SoloSoft</title><link>https://www.solosoft.dev/tags/scrapegraphai/</link><description>Recent content in ScrapeGraphAI on SoloSoft</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 01 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.solosoft.dev/tags/scrapegraphai/index.xml" rel="self" type="application/rss+xml"/><item><title>ScrapeGraphAI: LLM-Powered Web Scraping with Graph Logic</title><link>https://www.solosoft.dev/post/scrapegraph-ai-scraping-2026/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/post/scrapegraph-ai-scraping-2026/</guid><description>&lt;p&gt;Traditional web scraping is fragile. A scraper built around CSS selectors and XPath expressions breaks the moment the target website updates its HTML structure. Maintaining scrapers at scale becomes a constant game of catching up with layout changes, restructuring selectors, and re-testing pipelines. &lt;strong&gt;ScrapeGraphAI&lt;/strong&gt; takes a fundamentally different approach: instead of hard-coding extraction rules, it uses LLMs to understand page content semantically and extract the data you actually want.&lt;/p&gt;
&lt;p&gt;The core idea is that an LLM &amp;ndash; given a page&amp;rsquo;s rendered content and a description of what to extract &amp;ndash; can identify the relevant information without knowing the page&amp;rsquo;s CSS structure. This makes ScrapeGraphAI scrapers resilient to layout changes. A website redesign that would break a traditional scraper barely registers: the LLM simply reads the new layout and finds the same information.&lt;/p&gt;</description></item></channel></rss>