<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Data and Document Extraction on DyCoAI | AI and Me</title><link>https://www.dycoai.com/tags/data-and-document-extraction/</link><description>Recent content in Data and Document Extraction on DyCoAI | AI and Me</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 17 Sep 2026 09:05:00 +0800</lastBuildDate><atom:link href="https://www.dycoai.com/tags/data-and-document-extraction/index.xml" rel="self" type="application/rss+xml"/><item><title>Data &amp; Document Extraction as an Agentic Skill</title><link>https://www.dycoai.com/notes/agentic-skill-data-and-document-extraction/</link><pubDate>Thu, 17 Sep 2026 09:05:00 +0800</pubDate><guid>https://www.dycoai.com/notes/agentic-skill-data-and-document-extraction/</guid><description>&lt;p&gt;&lt;strong&gt;Data &amp;amp; Document Extraction&lt;/strong&gt;, as an agentic skill, is the capability of an AI agent to pull structured values, named entities, dates, amounts, statuses, clauses, and other factual elements out of unstructured or semi-structured materials such as documents, forms, emails, scanned pages, images, tables, and files.&lt;/p&gt;
&lt;p&gt;It goes beyond simply locating a source by converting raw content into machine-readable fields, records, or annotations that can support later operations such as comparison, verification, summarization, analysis, reporting, or workflow automation.&lt;/p&gt;</description></item></channel></rss>