Your team runs a customer support chat application on Azure AI Foundry. Most incoming queries are simple FAQ-style questions that a small, low-cost model can answer accurately, but roughly 15% are complex, multi-step reasoning questions that require a large frontier model to answer well. Leadership wants to minimize per-token cost without sacrificing answer quality on the hard questions, and the team does not want to build and maintain a custom classifier. Which approach should you implement?