In the ongoing revolution of Artificial Intelligence (AI), Machine Learning (ML), and Large Language Models (LLMs), Python has become the go-to language for many data scientists and ML engineers. However, as enterprises shift from experimental projects to mission-critical implementations, the priorities change. Stability, scalability, security, and cost efficiency become paramount.
This is where Java excels. With its decades-long track record, mature ecosystem, and enterprise-grade performance, Java is ideally suited for training AI/ML models and deploying LLM-powered applications. Many organizations are turning to Java to ensure reliability at scale, seamless integration with existing systems, and long-term maintainability benefits.
From leveraging advanced libraries like Deep Java Library (DJL) and Deep Netts to integrating AI capabilities into existing Java applications, the possibilities are vast. Paired with Azul’s enterprise-ready Java platforms, businesses can innovate faster, run smarter, and reduce costs while building the future of AI.
Java remains pervasive in enterprise environments due to its platform independence, robustness, and mature ecosystem of tools and libraries making it ideal for AI and ML integration without overhauling tech stacks
While Python often gets the spotlight in AI development for its extensive library ecosystem, Java offers unique advantages especially when building enterprise-grade, production-ready AI systems.
Java’s Just-In-Time (JIT) compiler optimizes code in real time, adapting it to the system it’s running on for peak performance. This means your AI workloads run efficiently across platforms, without performance bottlenecks. With Azul Platform Core builds of OpenJDK, the performance edge goes even further thanks to:
You can leverage your current Java-based infrastructure, developer expertise, and DevOps processes to build AI solutions that integrate effortlessly into existing applications. From security and monitoring tools to deployment pipelines, Java supports a smooth transition from concept to production.
Java is known for producing robust, scalable, and maintainable code. Its static typing helps catch errors early at compile time, reducing production bugs. Modern language updates like records and pattern matching, simplify complex logic and improve readability. And with powerful IDEs and refactoring tools, evolving large AI codebases is faster and less error-prone.
As AI and ML workloads become more complex, enterprises need a fast, secure, and scalable Java runtime. Azul, the world’s largest independent Java runtime provider, delivers exactly that, enabling organizations to run AI-powered applications with enterprise-grade performance and reliability.
Azul Platform Core provides a fully certified, Java SE–compliant runtime that delivers seamless compatibility. This ensures AI and ML models built in Java run smoothly in production, with predictable performance and lower licensing costs. Many enterprises adopt Azul to avoid vendors lock-in, ensure long-term support (LTS), and keep their Java stack future-ready.
For large AI/ML training and inference workloads, Azul Platform Prime offers advanced Just-In-Time (JIT) compilation and memory management techniques that can dramatically reduce infrastructure footprints. Organizations have reported up to 50% lower cloud compute costs and significantly improved latency critical for real-time AI decision-making and LLM-based services.
With the Azul Intelligence Cloud, enterprises gain unprecedented visibility into Java applications running in production. This includes:
AI systems often integrate with sensitive enterprise data, making security non-negotiable. Azul’s runtime platforms are continuously patched for vulnerabilities, ensuring AI/ML services stay compliant with industry regulations (e.g., GDPR, HIPAA, PCI DSS).
By combining Java’s cross-platform stability with Azul’s optimization and observability capabilities, enterprises can confidently scale AI and ML projects from pilot to full production whether on-premises, in the cloud, or at the edge. This positions Azul as a critical enabler for organizations looking to integrate AI into their core business operations without compromising on cost, performance, or security.
While Python has been instrumental in rapidly prototyping and advancing AI, ML, and LLM technologies, Java stands out when it comes to building mature, enterprise-grade production systems. Its performance, stability, and seamless integration into existing enterprise environments make it a powerful choice for the next wave of intelligent applications.
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As a trusted Zones partner, Azul powers tens of millions of servers and devices worldwide, including deployments in 36% of the Fortune 100 and all of the top 10 global companies. This Java SE–compliant runtime delivers the stability, security, and cost efficiency modern enterprises need.
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