https://www.infoq.com InfoQ AI, ML & Data Engineering Articles feed https://www.infoq.com/articles/ai-code-guardian/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=AI%2C+ML+%26+Data+Engineering-articles <img src="https://res.infoq.com/articles/ai-code-guardian/en/headerimage/ai-code-guardian-header-1776157217464.jpg"/><p>CodeGuardian is an MCP server that extends AI coding assistants with comprehensive code quality and security analysis capabilities. By implementing eleven specialized tools, CodeGuardian enables developers to access enterprise-grade analysis directly through their AI assistant, eliminating context-switching and reducing friction in adopting secure coding practices.</p> <i>By Madhvesh Kumar, Deepika Singh</i> Model Context Protocol (MCP) AI Assisted Coding AI, ML & Data Engineering article Tue, 28 Apr 2026 09:00:00 GMT https://www.infoq.com/articles/ai-code-guardian/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=AI%2C+ML+%26+Data+Engineering-articles Madhvesh Kumar, Deepika Singh 2026-04-28T09:00:00Z /articles/ai-code-guardian/en https://www.infoq.com/articles/mcp-java-architectural-strategy-llm-integrations/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=AI%2C+ML+%26+Data+Engineering-articles <img src="https://res.infoq.com/articles/mcp-java-architectural-strategy-llm-integrations/en/headerimage/mcp-java-architectural-strategy-llm-integrations-header-1776772947180.jpg"/><p>Discover how the Model Context Protocol (MCP) Java SDK is establishing a new architectural discipline for enterprise LLM integrations. By defining explicit contracts and leveraging MCP servers as anti-corruption layers, it ensures governance, loose coupling, and security alignment with the JVM ecosystem and existing operational practices, moving integrations beyond fragility to resilience.</p> <i>By Matteo Rossi</i> Java Large language models AI Development Memcached Development AI, ML & Data Engineering article Mon, 27 Apr 2026 11:00:00 GMT https://www.infoq.com/articles/mcp-java-architectural-strategy-llm-integrations/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=AI%2C+ML+%26+Data+Engineering-articles Matteo Rossi 2026-04-27T11:00:00Z /articles/mcp-java-architectural-strategy-llm-integrations/en https://www.infoq.com/articles/orchestrating-agentic-multimodal-ai-pipelines-apache-camel/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=AI%2C+ML+%26+Data+Engineering-articles <img src="https://res.infoq.com/articles/orchestrating-agentic-multimodal-ai-pipelines-apache-camel/en/headerimage/orchestrating-agentic-multimodal-ai-pipelines-apache-camel-header-1776763980414.jpg"/><p>In this article, author Vignesh Durai discusses how agentic and multimodal AI systems can be engineered using Apache Camel and LangChain4j technologies. The key components in the solution include LLM-based reasoning, retrieval-augmented generation (RAG), and image classification.</p> <i>By Vignesh Durai</i> Artificial Intelligence LangChain Data Pipelines Apache Camel Large language models AI, ML & Data Engineering article Fri, 24 Apr 2026 09:00:00 GMT https://www.infoq.com/articles/orchestrating-agentic-multimodal-ai-pipelines-apache-camel/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=AI%2C+ML+%26+Data+Engineering-articles Vignesh Durai 2026-04-24T09:00:00Z /articles/orchestrating-agentic-multimodal-ai-pipelines-apache-camel/en