<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data Parsing on SoloSoft</title><link>https://www.solosoft.dev/tags/data-parsing/</link><description>Recent content in Data Parsing 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/data-parsing/index.xml" rel="self" type="application/rss+xml"/><item><title>OmniParse: Open-Source Universal Data Parsing for GenAI Pipelines</title><link>https://www.solosoft.dev/post/omniparse-data-ingestion-2026/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/post/omniparse-data-ingestion-2026/</guid><description>&lt;p&gt;Modern GenAI applications consume data in many forms &amp;ndash; PDFs, spreadsheets, images, audio recordings, and video files. Building a RAG pipeline that can ingest all of these formats and produce clean, consistent structured output is a significant engineering challenge. &lt;strong&gt;OmniParse&lt;/strong&gt; solves this problem by providing a universal data ingestion platform that converts any unstructured data into structured Markdown, ready for vector embedding and retrieval.&lt;/p&gt;
&lt;p&gt;Developed by adithya-s-k, OmniParse uses specialized parsing pipelines for each data type, backed by open-weight models that run entirely locally. This means no data leaves your environment, no API calls incur ongoing costs, and no third-party services are involved in processing sensitive documents.&lt;/p&gt;</description></item></channel></rss>