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      <title>Article: Building a RAG Application with Spring Boot, Spring AI, MongoDB Atlas Vector Search, and OpenAI</title>
      <link>https://www.infoq.com/articles/rag-with-spring-mongo-open-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=MongoDB-articles</link>
      <description>&lt;img src="https://res.infoq.com/articles/rag-with-spring-mongo-open-ai/en/headerimage/rag-with-spring-mongo-open-ai-header-1761292137478.jpg"/&gt;&lt;p&gt;The RAG paradigm redefines AI: it combines generative models and business data for accurate, contextualised responses. The article shows how to integrate Spring Boot, Spring AI, MongoDB Atlas and OpenAI into a powerful and flexible pipeline capable of transforming the way businesses access and create value from data, with applications ranging from finance and healthcare to customer service.&lt;/p&gt; &lt;i&gt;By Matteo Rossi&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Artificial Intelligence</category>
      <category>MongoDB</category>
      <category>Retrieval-Augmented Generation</category>
      <category>Java</category>
      <category>Spring</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Mon, 27 Oct 2025 11:00:00 GMT</pubDate>
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      <dc:creator>Matteo Rossi</dc:creator>
      <dc:date>2025-10-27T11:00:00Z</dc:date>
      <dc:identifier>/articles/rag-with-spring-mongo-open-ai/en</dc:identifier>
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