Unverified50% confidenceFactExact time
Search systems typically use an embedding model to encode queries and documents into vectors separately and then retrieve candidate results via vector similarity; this process is called semantic retrieval or vector retrieval.
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10/20/2026
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UnverifiedDeterministic retrieval refers to a retrieval method that returns exactly the same result set every time given the same query and the same knowledge base; typical implementations include exact path queries based on graph traversal, exact matching based on primary keys/aliases, and structured filtering under rule constraints.79% similarVerifiedIn the knowledge retrieval stage, the user's question is converted into a query vector via an embedding model, similarity is computed against the text chunk vectors in the knowledge base (typically using cosine similarity), and the top-K segments are returned by ranking.77% similarUnverifiedVector search works by embedding text into a high-dimensional space and using similarity measures to find the segments closest to the query.76% similarUnverifiedTool search is typically implemented using vector embedding technology, retrieving the most relevant tools by semantic similarity and injecting them into the context.75% similarUnverifiedThe solution employs agentic retrieval to give the retrieval process active reasoning capabilities, and uses the Cypher query language to perform structured queries on the graph.75% similar
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