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      <title>Article: Bringing AI Inference to Java with ONNX: a Practical Guide for Enterprise Architects</title>
      <link>https://www.infoq.com/articles/onnx-ai-inference-with-java/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=ONNX-articles</link>
      <description>&lt;img src="https://res.infoq.com/articles/onnx-ai-inference-with-java/en/headerimage/Bringing-AI-Inference-to-Java-with-ONNX-image-header-1759229686552.jpg"/&gt;&lt;p&gt;Java applications can now run transformer-based AI models directly within the JVM—without Python, REST wrappers, or microservices. This guide shows how to integrate ONNX-powered inference with tokenizer support, GPU acceleration, modular deployment, and observability, enabling architects in regulated domains to adopt AI without disrupting compliance or CI/CD workflows.&lt;/p&gt; &lt;i&gt;By Syed Danish Ali&lt;/i&gt;</description>
      <category>Java</category>
      <category>ONNX</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
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      <pubDate>Fri, 03 Oct 2025 09:00:00 GMT</pubDate>
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      <dc:creator>Syed Danish Ali</dc:creator>
      <dc:date>2025-10-03T09:00:00Z</dc:date>
      <dc:identifier>/articles/onnx-ai-inference-with-java/en</dc:identifier>
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