Key takeaways
AI applications use a single endpoint to handle multiple complex tasks: classification, urgency scoring, customer-facing drafting, and long-form summarization.
This does not account for varying cost, latency, and quality requirements.
Building a FastAPI and using serverless inference infrastructure makes it possible to address these requirements through effective routing.
Most AI applications start with a single model hard-coded into the app. That works well for a prototype, but it breaks down the moment a single endpoint has to handle multiple complex task categories: classification, urgency scoring, customer-facing drafting, and long-form summarization all benefit from different model choices. Those tasks do not share the same cost, latency, or quality requirements.
