The Architecture Behind Sub-500ms Response Times

## The Challenge of Low-Latency AI Serving LLM responses with sub-500ms first-token latency at enterprise scale is genuinely hard. The inference itself takes time, the retrieval pipeline adds latency, and network round-trips compound everything. Here's how we built CCA's architecture to meet this bar consistently. ## Streaming-First Design We never wait for the full response before sending bytes to the browser. Every CCA widget uses server-sent events (SSE) to stream tokens as the model generates them. The perceived latency is effectively the time to first token, which is what makes the widget feel instant rather than laggy. ## Tiered Retrieval Pipeline Our RAG pipeline runs three retrieval strategies in parallel: 1. **Semantic search** on embedded document chunks (primary) 2. **Keyword BM25 search** for exact-match queries 3. **Cached FAQ lookup** for high-frequency questions The fastest result wins. Repeat questions are served from cache, cutting response time further. ## Distributed Infrastructure Widget traffic is routed to the nearest available inference endpoint, keeping round-trip time low regardless of where your customers are. ## What This Means for Your Business Speed isn't just a technical metric — it's a product experience. At 500ms, the widget feels instantaneous. At 2 seconds, it feels slow. At 5 seconds, customers click away. We obsess over latency because your customers' attention is non-renewable.