AI Infrastructure Glossary
AI infrastructure is the layer of vector databases, knowledge graphs, structured data, and machine-readable endpoints that let AI models retrieve, understand, and reuse information. This collection defines the core terms, including RAG, embeddings, and semantic search, and links to the full explainer on what AI infrastructure means for websites.
A
- AI Infrastructure
- The systems that let AI models retrieve, understand, and reuse information: vector databases, knowledge graphs, structured data, and machine-readable endpoints.
R
- RAG (Retrieval-Augmented Generation)
- A technique where an AI system retrieves relevant information from external sources before generating a response, grounding its output in real data rather than model memory alone.
V
- Vector Database
- A database that stores information as mathematical vector representations (embeddings), enabling semantic search by meaning rather than exact keyword matching.