  Although there has been a growing interest among industries to integrate
generative LLMs into their services, limited experiences and scarcity of
resources acts as a barrier in launching and servicing large-scale LLM-based
conversational services. In this paper, we share our experiences in developing
and operating generative AI models within a national-scale search engine, with
a specific focus on the sensitiveness of user queries. We propose a taxonomy
for sensitive search queries, outline our approaches, and present a
comprehensive analysis report on sensitive queries from actual users.
