What Is a RAG Pipeline?

A RAG (retrieval-augmented generation) pipeline is a comprehensive infrastructure system designed to process and deliver data from source systems to language models at query time, including stages such as ingesting, chunking, embedding, storing, retrieving, and generating. While discussions often focus on retrieval and generation, the initial ingestion stage is crucial but frequently overlooked, leading to potential failures in production if not properly managed. Ingestion involves connecting to various data sources, handling real-time or polled updates, and ensuring continuous synchronization to prevent outdated context from degrading response quality. Challenges arise from silent failures, unstable chunk IDs, and permission issues, making the ingestion layer complex and costly to maintain. Unified offers solutions for managing the ingestion layer by providing authorized reads from numerous APIs, event-driven change detection, and checkpointed delivery for robust and reliable data processing, allowing teams to focus on retrieval and generation optimization. The document emphasizes the importance of carefully considering whether to build a custom ingestion layer or leverage existing infrastructure due to the unforeseen complexities and maintenance costs associated with building it from scratch.