Optimizing LLM Routing Latency in Real-Time Applications

Routing requests to multiple model endpoints sequentially adds massive latency. To make multi-agent systems production-ready, routing must occur in under 1.2 seconds. At v43.ai, we accomplish this by executing lightweight semantic embedding classifiers at edge CDN locations. By running local models (like Ollama/Gemma) for initial routing logic, we classify the complexity of the incoming prompt instantly, dispatching the payload to the cloud APIs (Anthropic/OpenAI) in parallel before compiling responses. Edge caching and connection pooling cut downstream TCP roundtrip times, securing a fast user experience.