AI Glossary
Embedding
Also known as: Vector embedding · Semantic vector
An embedding is a list of numbers that represents the meaning of a text, so that texts with similar meaning end up close together in vector space.
What it’s for
Embeddings enable search by meaning, not just exact words. “How do I cancel my plan” and “I want to end my subscription” land close together even with no words in common.
Where they show up
- Semantic search and RAG
- Content recommendation
- Clustering and duplicate detection
In practice
Embeddings live in a vector store (such as pgvector on Postgres). Switching embedding models means re-processing the whole corpus, so choose carefully and version it.
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AI for SREs
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