Part 11: RAG team play with Spring AI
This blog talks about Kong’s potential for Retrieval-Augmented Generation (RAG) implementations. RAG is a technique that improves large language models by adding real-time, enterprise-specific data retrieval, improving response accuracy and relevance. The team play between Kong AI Gateway and Spring AI enables seamless integration and optimization of generative AI RAG workflows within enterprise environments.Part 10: AI Gateway
This blog details how Kong API Gateway functions as an AI Gateway, providing the necessary features to manage AI integrations securely and efficiently. Kong offers a complete, high-quality middleware solution that makes AI development easier by removing the need for many special tools and frameworks. It also supports language independence to avoid any limits. Additionally, the new AI plugins empower organizations to mitigate AI risks and uphold ethical AI practices.Part 9: Serverless functions - Who responded?
In our previous blog posts in the Kong Gateway series, we explored various security aspects, particularly focusing on token-related issues and their solutions involving both Kong and custom-built plugins. Today, we dive deeper into another coding variant within the gateway: Kong serverless functions. We will use a real-world “Who Responded?” example to demonstrate how effectively a root cause analysis approach can be supported with minimal effort.Visit NTT DATA
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