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 includes an optional toolkit called the Oracle AI Optimizer and Toolkit (the “AI Optimizer”). It provides a streamlined environment for developers and data scientists to explore Generative AI (GenAI) with Retrieval-Augmented Generation (RAG). By integrating Oracle Database AI Vector Search and SelectAI, the AI Optimizer enables users to enhance existing large language models (LLMs) via RAG, improving performance and accuracy while mitigating issues such as knowledge cutoffs and hallucinations. With the included API server, you can turn experiments into highly scalable services or easily generate microservice code in Java (Spring AI) or Python (LangChain) for independent deployment. Integration with Oracle AI Database (Vector Search) provides the ability to manage millions of chunks and embedding vectors, delivering the scalability to meet enterprise 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 includes an optional toolkit called the Oracle AI Optimizer and Toolkit (the “AI Optimizer”). It provides a streamlined environment for developers and data scientists to explore Generative AI (GenAI) with Retrieval-Augmented Generation (RAG). By integrating Oracle Database AI Vector Search and SelectAI, the AI Optimizer enables users to enhance existing large language models (LLMs) via RAG, improving performance and accuracy while mitigating issues such as knowledge cutoffs and hallucinations. With the included API server, you can turn experiments into highly scalable services or easily generate microservice code in Java (Spring AI) or Python (LangChain) for independent deployment. Integration with Oracle AI Database (Vector Search) provides the ability to manage millions of chunks and embedding vectors, delivering the scalability to meet enterprise demands.