Retrieval & data
Semantic search
Definition
Semantic search finds results by meaning rather than exact keywords, using embeddings to compare concepts. It matches "how do I get my money back" to a document titled "Refund Policy".
Keyword search requires shared vocabulary between query and document. Semantic search compares embedding vectors, so it matches paraphrases, synonyms and conceptually related phrasing.
The trade-off is that semantic search can be too fuzzy. It sometimes misses exact-match requirements — product codes, error numbers, specific names — precisely because it is looking at meaning rather than characters.
The strongest production systems use hybrid retrieval: run both keyword (BM25) and semantic search, then combine and re-rank. This captures exact matches and conceptual matches together.
Related terms
Embedding
An embedding is a list of numbers representing the meaning of a piece of text, such that semantically similar texts have mathematically similar vectors. Embeddings make meaning-based search possible.
Vector database
A vector database stores embeddings and finds the most similar ones to a query vector quickly. It is the retrieval layer of most RAG systems. Examples include Pinecone, Weaviate, Qdrant and pgvector.
RAG (Retrieval-Augmented Generation)
RAG retrieves relevant passages from your own documents and inserts them into the prompt before the model answers. It grounds responses in your data, cuts hallucination, and needs no retraining.
Reranking
Reranking takes an initial set of retrieved candidates and reorders them with a more accurate but slower model. It is one of the cheapest ways to materially improve RAG quality.
Chunking
Chunking splits documents into smaller passages before embedding them for retrieval. Chunk size is a key quality lever: too large dilutes relevance, too small loses the context needed to make sense.
Knowledge cutoff
A model's knowledge cutoff is the date after which it has no training data. It cannot know about events, releases or prices after that point unless given the information in the prompt or via search.
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