Semantic Router: A Five-Branch Context-Aware Model Routing System for AI Agents
We present Semantic Router, a production-grade intelligent routing system for AI agents that automatically selects the optimal language model based on conversational context. The system implements a four-layer detection pipeline and routes messages to one of four specialized model pools via a five-branch decision framework. Key innovations include: a trigger_groups_all mechanism for non-contiguous multi-keyword matching, a dual-channel scoring architecture combining semantic embeddings with entity overlap, a multi-layer C-auto deadlock prevention mechanism, and session isolation for background Cron jobs. Deployed in production on OpenClaw across multiple messaging channels, the system achieves >95% routing accuracy with <50ms latency overhead using a fully local, privacy-preserving embedding backend.


