Inspiration
We got the motivation for this idea by noticing how often emotional eating quietly affects people’s daily lives. It’s a common issue that impacts focus, confidence, and overall well-being, yet it’s rarely talked about and often overlooked. At the same time, AI is underutilized in supporting emotional well-being, especially when it comes to eating habits. We wanted to create something that makes support more accessible and helps people build real, lasting habits through awareness and reflection.
What it does
Alia provides real-time, empathetic guidance on emotional eating, using users’ journal entries, mood patterns, and environment data to offer personalized support.
How we built it
Frontend: Next.js AI & Embeddings: Gemini, LangChain Database & Authentication: Supabase, Datastax
Challenges we ran into
Building a real-time RAG system that processes sensitive user data in real-time while delivering timely, relevant guidance.
Accomplishments that we're proud of
Successfully implementing a RAG system that integrates both user context and scraped relevant data regarding and delivers personalized, empathetic AI support. We are also proud of building a fully functional website that has the potential to genuinely help people, support their well-being, and make a meaningful difference in their daily lives.
What we learned
How to leverage LangChain and vector databases for contextual AI retrieval and response generation.
What's next for NourishNote
Expanding personalization, improving context handling, and adding more actionable insights for emotional eating management. Adding observability and reliability infrastructure to maintain the application in production. Introducing personalized meditations as supportive response mechanisms. Incorporating community and peer support features to reduce stigma and increase motivation.
Built With
- datastax
- gemini
- langchain
- next.js
- supabase


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