How We Cut AI Token Costs by 70% in High-Volume Conversational Commerce
When building a WhatsApp ordering engine for restaurant chains, feeding the entire menu into the LLM on every turn created $0.10+ message costs and 4-second delays. Here is how we implemented Upstash Redis session caches and pgvector semantic filtering to slash latency and costs.