Routing agent tasks to the appropriate specialized agent or tool based on semantic understanding of the request, rather than keyword or category matching.
Semantic dispatch is the mechanism by which a multi-agent or multi-tool system routes incoming requests to the most appropriate handler based on deep semantic understanding rather than explicit keyword triggers, predefined categories, or rigid decision trees.
In traditional systems, routing is rule-based: if the request contains "billing" → route to billing handler; if it contains "support" → route to support handler. This approach breaks down with natural language inputs, which are ambiguous, varied, and often cross multiple domains.
Semantic dispatch uses embedding models to represent both the incoming request and each available agent/tool in a shared semantic space. Routing decisions are made based on semantic similarity, ensuring that "why was I charged twice last month?" correctly routes to the billing agent even without the word "billing."
Advanced semantic dispatch systems also consider:
- Agent capability scoring: How confident is each agent that it can complete this task?
- Context propagation: Routing with relevant context from earlier in the session
- Fallback chains: Ordered sequences of fallback handlers for low-confidence routing
- Ensemble routing: Decomposing ambiguous requests and routing sub-tasks to different specialists
Semantic dispatch is a key component of the "agentic router" pattern, where a lightweight coordination layer directs tasks to a network of specialized micro-agents.