Semantic Routing is an architectural technique that routes incoming prompts or API queries to specialized LLM models, vector databases, or cached responses based on intent and embedding similarity, rather than static keyword rules.
Semantic routing acts as an intelligent traffic gateway for modern LLM applications. Instead of executing every request against a high-cost frontier model, a semantic router converts incoming prompt text into a vector embedding and compares it against pre-defined intent clusters. Depending on vector distance, the system routes the request to the most cost-effective endpoint.
By evaluating prompt embeddings, a semantic router directs simple queries to lightweight models or instant cache hits, reserving large frontier models for complex multi-step reasoning.
Keyword routing relies on exact phrase matches, whereas semantic routing uses vector embeddings to understand intent even when queries use synonyms or alternative phrasing.
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