Lightweight agent router with reduced latency path selection across distributed compute nodes

Abstract

The systems and methods disclosed herein provide a lightweight artificial intelligence agent router that dynamically allocates tasks across a plurality of stateless AI agents. The router receives a task request and classifies it into one or more task types by comparing the request against historical task-agent pairings stored in a datastore. Each agent is registered in an agent registry that includes a metadata profile with performance metrics derived from prior executions. The router scores each agent by evaluating these performance metrics against the classified task type to rank the agents and select a subset of the agents whose scores satisfy a threshold value. The router determines an execution order by evaluating dependencies between sequential portions of the task request, thereby ensuring that outputs from earlier agents are available as inputs to subsequent agents. After task completion, the router updates the agent registry with execution results to adjust future routing decisions.