Embedding Generation

A 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.

A retrieval technique that uses dense vector embeddings to identify semantically relevant documents based on similarity in an embedding space.

A search technique that analyzes sentence meaning and intent rather than matching literal keywords.

The process of splitting documents into smaller, semantically meaningful segments to improve indexing, retrieval, and context generation for AI systems.