Not every AI decision needs a new model response. For routing, guardrails, and tool choice, embedding space can often provide a faster and more predictable answer than asking an LLM to deliberate every time.
What Sets It Apart
Semantic Router turns example utterances into routes and matches new inputs with configurable encoders and vector indexes. It sits below the agent layer, making repeated decisions cheaper and more inspectable.
Who Should Use It
Great fit if an app repeatedly classifies intent, chooses tools, or gates conversations before invoking a larger model. Look elsewhere if routing depends on deep reasoning over long context every time.
