Oracle Backend for Microservices and AI
Oracle Backend for Microservices and AI provisions a “backend as a service” with Oracle AI Database and other infrastructure components that operates on multiple clouds.
The service allows developers to build and deploy microservices in Spring Boot and other frameworks such as Helidon. Oracle Backend for Microservices and AI vastly simplify the task of building, testing, and operating microservices platforms for reliable, secure, and scalable enterprise applications.
Oracle Backend for Microservices and AI include an option toolkit called The Oracle AI Optimizer and Toolkit (the AI Optimizer). It provides a streamlined environment where developers and data scientists can explore the potential of Generative Artificial Intelligence (GenAI) combined with Retrieval-Augmented Generation (RAG) capabilities. By integrating Oracle Database AI VectorSearch and SelectAI, the AI Optimizer enables users to enhance existing Large Language Models (LLMs) through RAG. This method significantly improves the performance and accuracy of AI models, helping to avoid common issues such as knowledge cutoff and hallucinations. Oracle Ai Optimizer and Toolkit. Turn your experiment into a highly scalable service with the API server included or easily generate microservices code in Java (Spring AI) or Python (LangChain) to deploy as independent microservices. Integration with Oracle AI Database 26ai provides the ability to manage millions of chunks and embedding vectors, giving you the scalability to meet your demands.
The service allows developers to build and deploy microservices in Spring Boot and other frameworks such as Helidon. Oracle Backend for Microservices and AI vastly simplify the task of building, testing, and operating microservices platforms for reliable, secure, and scalable enterprise applications.
Oracle Backend for Microservices and AI include an option toolkit called The Oracle AI Optimizer and Toolkit (the AI Optimizer). It provides a streamlined environment where developers and data scientists can explore the potential of Generative Artificial Intelligence (GenAI) combined with Retrieval-Augmented Generation (RAG) capabilities. By integrating Oracle Database AI VectorSearch and SelectAI, the AI Optimizer enables users to enhance existing Large Language Models (LLMs) through RAG. This method significantly improves the performance and accuracy of AI models, helping to avoid common issues such as knowledge cutoff and hallucinations. Oracle Ai Optimizer and Toolkit. Turn your experiment into a highly scalable service with the API server included or easily generate microservices code in Java (Spring AI) or Python (LangChain) to deploy as independent microservices. Integration with Oracle AI Database 26ai provides the ability to manage millions of chunks and embedding vectors, giving you the scalability to meet your demands.