Building AI applications that can interact with private data is a common goal for many organizations. The challenge often lies in connecting large language models (LLMs) with proprietary datasets. A combination of Heroku Managed Inference and Agents and LlamaIndex provides an elegant stack for this purpose. This post explores how to use these tools to build retrieval-augmented generation (RAG) applications. We’ll cover the technical components, Use Cases and the development process, and how to get started. LlamaIndex for data orchestration LlamaIndex is an open-source framework for building context-aware LLM applications. Its core function is to orchestrate a retrieval-augmented generation (RAG) pipeline, which manages the entire data lifecycle for your application.…