AI product
Unifeast
A multi-turn dining recommendation chatbot that uses retrieval and rule-based allergen filtering outside the language model.
- Role
- AI/ML Engineer, Amazon University Engagement Programme
- Status
- Prototype
- Year
- 2025
Overview
A conversational dining recommendation prototype built during the Amazon University Engagement Programme.
Background
The prototype explored multi-turn dining recommendations while treating allergen safety as a system constraint rather than a generated suggestion.
Response
As sole developer, Qinxuan built three backend iterations, moving from the Bedrock console to LangChain. The final design keeps a rule-based allergen filter outside the language model.
Methods
Conversational AI · Retrieval-augmented generation · Rule-based allergen filtering · Prototype evaluation
Outcome
The project has a four-tab mobile demo, sample data, a small RAG implementation and an evaluation record.
Recognition
- Best Technical Implementation
Project materials
Project document being prepared for release.