MessMind AI
Vibe-coded campus dining feedback analytics: meal ratings, AI digests, and sentiment trends for mess managers.
Project intro
MessMind AI is a full-stack feedback analytics platform for campus dining (mess) scenarios. Students rate daily meals with tags, photos and voice notes in under 10 seconds; an AI pipeline classifies sentiment, extracts topics, judges severity and dedupes, then turns the stream into structured intelligence. The management dashboard shows average meal scores, rating trends, issue frequency, sentiment trends, recurring-issue detection and anomaly alerts, plus an AI-generated daily digest of top issues, positive signals and suggested fixes.
The project was built for a Vibe Coding Hackathon with React 19, Vite, Django 5.2, Django REST Framework, PostgreSQL and Tailwind CSS, with a Groq-powered AI pipeline and Google Antigravity as the development tool. It has 2 stars on GitHub and was last updated on October 16, 2026; the frontend is live on Vercel.
In the developer's own words in the README: "MessMind AI is a Vibe-Coded full-stack application built specifically for a Vibe Coding Hackathon."
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Tech stack
Project info
- Project category
- Analytics
- Project status
- Online
- Collaboration intent
- None