Hackathon idea: build anything AI-related, but make sensitive data safe to use

I work at Protegrity, and we’re running a U.S.-only virtual hackathon around secure AI pipelines. The basic idea is: build whatever you want, as long as it uses AI and has a real reason to handle sensitive data. Could be a RAG app, agent workflow, internal analytics tool, customer support bot, healthcare/finance demo, data engineering pipeline, synthetic data project, whatever. The creative part is up to you. The main challenge is showing how sensitive data should be protected across the workflow. For example: ingestion, embeddings, retrieval, inference, response generation, logs, or downstream analytics. I think it's an interesting problem. A lot of AI demos assume the data is already clean and safe, but real systems usually run into PII, financial data, customer records, or regulated data pretty quickly. Top prize is $10k cash. Also genuinely curious: does this kind of open-ended AI/security challenge sound interesting to builders here, or would you frame it differently?