AI Meal-Planning Product Development
Budget: $10,000 – $20,000 USD
I am building an AI Health and Nutrition product whose core promise is clear, actionable nutritional advice—specifically, smart meal planning that adapts to each user’s goals and dietary profile. The system should ingest user-supplied data (age, activity level, preferences, allergies), run it through a recommendation engine, and return balanced meal plans that are easy to follow and update in real time.
The scope covers:
• Designing or customising the algorithm that matches macro- and micro-nutrient targets to ingredient databases.
• Connecting that algorithm to an intuitive web or mobile interface so users can review, swap, or lock meals with a tap.
• Building in feedback loops that learn from user behaviour and continuously refine future meal suggestions.
• Ensuring every plan is labelled for allergens and common dietary restrictions (vegan, gluten-free, etc.).
Preferred stack: Python, TensorFlow or PyTorch for modelling, a clean React or Flutter front end, and a reliable food-nutrition database such as USDA or Open Food Facts. I’m open to alternatives if you can explain the trade-offs.
Acceptance criteria will include:
1. A working prototype that generates seven-day meal plans from sample profiles in under 30 seconds.
2. Nutrient balance within ±5 % of user goals.
3. Clear instructions for local deployment and an outline for scaling to production.
If this aligns with your expertise, tell me briefly how you would tackle data sourcing, personalisation logic, and UI hand-off. I’m ready to start as soon as we agree on milestones and timelines.
The scope covers:
• Designing or customising the algorithm that matches macro- and micro-nutrient targets to ingredient databases.
• Connecting that algorithm to an intuitive web or mobile interface so users can review, swap, or lock meals with a tap.
• Building in feedback loops that learn from user behaviour and continuously refine future meal suggestions.
• Ensuring every plan is labelled for allergens and common dietary restrictions (vegan, gluten-free, etc.).
Preferred stack: Python, TensorFlow or PyTorch for modelling, a clean React or Flutter front end, and a reliable food-nutrition database such as USDA or Open Food Facts. I’m open to alternatives if you can explain the trade-offs.
Acceptance criteria will include:
1. A working prototype that generates seven-day meal plans from sample profiles in under 30 seconds.
2. Nutrient balance within ±5 % of user goals.
3. Clear instructions for local deployment and an outline for scaling to production.
If this aligns with your expertise, tell me briefly how you would tackle data sourcing, personalisation logic, and UI hand-off. I’m ready to start as soon as we agree on milestones and timelines.