Diet X
An AI nutrition platform built on a normalized food-data engine.
Next.js
TypeScript
Python
MongoDB
Node.js
OpenAI
Diet X pairs a cleaned, structured nutrition database with an AI planning layer to turn goals and pantry items into precise, trackable meal plans.
Diet X
Diet X pairs a cleaned, structured nutrition database with an AI planning layer to turn goals and pantry items into precise, trackable meal plans.
The problem
Public nutrition datasets are inconsistent, full of duplicates, and hard to query reliably — which makes any app built on top of them fragile. Generic meal planners ignore real constraints like macros, budget, and what's already in your kitchen.
Architecture
A Python data-refinement pipeline ingests raw food datasets, deduplicates and normalizes them into a consistent schema, and loads them into MongoDB.
A Next.js app sits on top, with an AI layer that constrains LLM output against the structured database so plans are grounded in real numbers rather than hallucinated ones.
The model never invents nutrition facts — it plans within the bounds of verified database entries.
Features
- Refined, normalized food database — deduplicated and unit-consistent.
- Goal-aware meal planning that respects calorie and macro targets.
- Pantry-aware suggestions that work with what you already have.
- Live macro tracking with progress against daily targets.
