Guest Feedback Collection and Summary Service for Hospitality Teams

Added Jun 2025 3 design docs

Hotels, restaurants, and short-stay operators live and die by guest sentiment, yet most small hospitality businesses handle feedback with a spreadsheet at best. Comment cards, post-stay emails, and review-site messages pile up unread, and by the time a pattern such as slow check-in or cold breakfast becomes obvious, it has already cost bookings. Managers need feedback collected in one place and distilled into something they can act on before the next weekend rush. The intern builds a lightweight service that does both. Using Python and FastAPI, the intern creates endpoints for submitting guest feedback from web forms or imports, storing it with metadata such as date, location, and service area. On top of that store, OpenAI models generate concise summaries: what guests praised, what they complained about, and how sentiment is trending week over week, retrievable through a simple summary endpoint a manager can check each morning. The project is deliberately scoped for an early-stage developer and teaches the foundations properly: designing REST endpoints, validating and persisting incoming data, calling a language model API with well-constructed prompts, and shaping model output into consistent, digestible reports. The intern finishes with a genuinely deployable tool and a clear grasp of how agentic AI creates value in a service business.

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