Core AI Concepts
Embedding
An embedding is a numeric representation of text's meaning, used for semantic search and RAG — derived from your content, and sensitive in proportion to it.
An embedding converts text into a vector — a list of numbers — positioned so that similar meanings land near each other. Semantic search, recommendation, and RAG retrieval all run on embeddings stored in vector databases.
Embeddings are derived data, not anonymized data: research has shown substantial text reconstruction from vectors, and the embedding pipeline itself sends source text to whichever provider computes them. Treat embedding stores with the sensitivity of the content they encode.
Where this shows up
Related terms
See it in your own organization.
Sanitized AI inventories the AI tools in use and redacts sensitive data from prompts before it leaves.