LLM Integration
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Enterprise Java
Choosing a Java LLM Integration Strategy in 2026: Spring AI 1.1 vs LangChain4j vs Direct API Calls
Three genuinely different architectural postures — and a practical framework to help your team choose the right one before you…
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Enterprise Java
Getting Started with the Java Model Context Protocol (MCP) SDK
The rapid growth of AI-powered applications has created a need for standardized ways to connect models with external tools, services,…
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Enterprise Java
Spring AI Integration: Building Intelligent Java Applications
The AI revolution isn’t just for Python developers anymore. With Spring AI quickly becoming the starting point when Java developers…
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Core Java
Integrating a Java Backend with AI/LLM Services: Best Practices, Latency & Safety
The integration of large language models into enterprise Java applications has moved from experimental to essential. Organizations running Java backends…
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Enterprise Java
Building an AI Agent in Java with the Embabel Framework
Artificial Intelligence (AI) is steadily moving from research labs into production systems, and developers are seeking frameworks that facilitate easier…
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Enterprise Java
Java Langchain MongoDB Example
This article explores how to build an AI-powered chatbot using Langchain4j, MongoDB Atlas, and Ollama running locally. This solution leverages…
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