Author(s): GenAI Lab Originally published on Towards AI. Learn how to combine Neo4j knowledge graphs with LangChain to build accurate, explainable, and production-ready Retrieval-Augmented Generation (RAG) systems. Retrieval-Augmented Generation (RAG) has quickly become the go-to architecture for making Large Language Models (LLMs) …

Author(s): GenAI Lab Originally published on Towards AI. Building on our previous guide, let’s add enterprise-grade security to your AI workflows In Part 1, we built a basic LangGraph architecture via FastAPI. But before deploying to production, we need robust authentication and …

Author(s): GenAI Lab Originally published on Towards AI. Building on our previous guide, let’s add enterprise-grade security to your AI workflows In Part 1, we built a basic LangGraph architecture via FastAPI. But before deploying to production, we need robust authentication and …

Author(s): GenAI Lab Originally published on Towards AI. Introduction As Large Language Models (LLMs) become increasingly capable, building intelligent systems that can reason, interact, and maintain context across multiple steps is more important than ever. But orchestrating these multi-step workflows is no …

Author(s): GenAI Lab Originally published on Towards AI. Google’s A2A Protocol: A New Standard for Agent-to-Agent Communication in AI AI agents are no longer isolated experiments — they’re evolving into complex ecosystems. From multi-agent frameworks like LangGraph to enterprise-scale orchestration systems, the …