What is an Embedding?
An embedding is a representation of text (or image, audio) as a vector — a list of hundreds or thousands of floating-point numbers. The embedding model converts a sentence into a point in multi-dimensional space where semantically similar texts have close coordinates.
How does it work?
The sentences "AI in business" and "artificial intelligence for companies" will produce similar vectors despite different words — because their meaning is similar. Embedding models are trained on billions of text pairs to learn these semantic relationships.
Enterprise applications
Embeddings are the foundation of: semantic search, RAG (knowledge base indexing), deduplication (detecting similar documents), classification (grouping tickets, emails, feedback), and recommendations. Embedding quality determines the quality of all downstream processes.