What is Semantic Search?

Explained

Semantic search finds content by meaning rather than keyword matching. It uses embeddings to compare query and documents by conceptual similarity, improving recall and relevance.

Decision guides that use this term

• RAG vs enterprise search: do your people need answers or documents?

Further reading

• Vector Databases for RAG: Powering Semantic Search for LLMs

Related terms

• Big Data Large volumes of data requiring specialized tools; feedstock for training AI models.
• Context Engineering Designing what the model sees—retrieval, memory, summaries, and window budgeting.
• Corpus Collection of documents used to train or feed a system (e.g., RAG).
• Data Lake Repository that stores raw data; source for analytics and ML.
• Data Pipeline Automated flow of data from sources to models or applications.
• Extraction Process of extracting structured information from text (entities, relationships).