Question

A customer support team receives tickets in multiple languages. The GenAI application must: (1) detect and translate each ticket into English, (2) classify the ticket into a support category, and (3) generate a concise English summary for the support agent. The team wants a maintainable design where each step can be tested and swapped independently, and where a failure or low-confidence result in one step can be inspected before the next step runs. Which design approach best meets these requirements?

Accepted Answer

Decompose the workflow into a sequential chain of discrete steps (translate → classify → summarize), where the output of each step is passed as input to the next and each step is an independently testable component.

Answer

Build a single large prompt that instructs one LLM call to translate, classify, and summarize the ticket all at once, returning a combined result.

Answer

Fine-tune a single model on translated, classified, and summarized examples so the model performs all three tasks implicitly without separate steps.

Answer

Deploy three completely independent applications that each process the raw ticket in parallel, then merge their unrelated outputs at the end.