Indexing Pipeline
Also called: Document Indexing Pipeline
A sequence of processes that ingests, cleans, transforms, chunks, enriches, embeds, and indexes data into a searchable store, preparing documents and other content for efficient retrieval by AI applications.
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Related terms
A component that ingests documents from various sources and formats, extracts their content, and prepares them for indexing and retrieval pipelines.
Document ChunkingThe process of splitting documents into smaller, semantically meaningful segments to improve indexing, retrieval, and context generation for AI systems.
Embedding ModelA machine learning model that converts text, images, audio, or other data into dense numerical vector representations that capture semantic meaning for retrieval, similarity search, and related AI tasks.
Retrieval-Augmented GenerationRAGAn architectural pattern that enhances generative model responses by retrieving relevant information from external knowledge bases.