AI Meal Planner

Case Study

AI Meal Planner

Healthy Eating, Made Effortless With AI

Industry

HealthTech

Product Type

Mobile App

Duration

6 Month

Year

2025

Project Overview

AI Meal Planner is a next-generation, AI-powered meal planning and nutrition management platform designed to help families eat healthier with less effort. The app automates the entire food journey — plan → shop → log → score → nudge — using a conversational AI assistant that creates personalised weekly meal plans, generates smart shopping lists, infers nutrition from voice logs, and scores daily nutritional habits for each family member. AI Meal Planner is built to be friendly, proactive, and family-centric, making healthy eating simple, intuitive, and sustainable.

Business Challenges

Families often face major hurdles when trying to maintain healthy eating habits:

  • Lack of Personalised Nutrition Guidance: Most tools offer generic plans, failing to consider allergies, beliefs, budgets, age-based needs, or family preferences.
  • Time-consuming Meal Planning: Parents struggle to plan weekly meals, swap recipes quickly, or track nutritional balance across the family.
  • Manual & Fragmented Tracking: Logging meals and monitoring nutrition often require multiple apps, spreadsheets, or calorie calculators.
  • Limited Flexibility: Meal plan adjustments, last-minute swaps, or handling dietary conflicts are hard without proper AI automation.
  • Low Engagement in Existing Health Apps: Static apps fail to engage users over time, causing drop-off in healthy eating habits.

AI Meal Planner needed to solve these problems through an AI-first, family-friendly, and highly intuitive product experience.

Solutions

AI Meal Planner delivers an end-to-end process to simplify healthy meal planning and tracking:

  • Onboarding & Personalisation: Users start with a quick, passwordless sign-up process. They provide family details, preferences, goals, and dietary restrictions to customise the meal plan for each member.
  • Meal Plan Generation: AI Meal Planner automatically generates weekly meal plans based on user preferences, family goals, and available ingredients. Users can swap meals or adjust based on new goals or dietary changes.
  • Smart Shopping List: The AI translates meal plans into a smart shopping list. Ingredients are categorised, quantities adjusted, and pack sizes suggested to reduce waste. Users can modify the list via text or voice.
  • Meal Logging & Nutrition Scoring: Users log meals with voice or text. AI Meal Planner infers the meals and portions, scoring daily nutrition across multiple dimensions (calories, protein, fibre, etc.). The app tracks individual and family nutrition progress over time.
  • Conversational AI Assistant (Tucki): The proactive AI assistant handles meal swaps, answers nutrition questions, and assists with meal planning. It also provides real-time feedback and nudges to keep users on track.
  • Daily Dashboard & Insights: The dynamic dashboard shows daily and weekly nutrition progress, highlights key actions (e.g., streaks, completed meals), and suggests healthy habits based on user data.
  • Gamification & Rewards: Points, streaks, and achievements are integrated to engage users. Users can track their progress through daily, weekly, and monthly streaks.
  • Subscription & Payment: The app includes a flexible subscription model (monthly/annual) via RevenueCat, with a soft paywall after onboarding and a hard paywall after significant user engagement.

Results & Outcome

The beta release delivered strong improvements in user experience and operational efficiency

90%

Reduction in time required to generate a weekly meal plan

clock2 (1) 2

3X

Increase in user engagement after adding AI chat + voice logging

80%

Improvement in nutrition awareness among pilot families

400+

Weekly meal logs submitted during beta testing

100%

Onboarding completion pass rate with 3 min median time

95%

Shopping list accuracy after unit normalisation & consolidation

Tech Stack

The Engine Behind AI Meal Planner

Figma

UI/UX Design

React Native

Frontend

Tailwind

Frontend

TypeScript

Frontend

Node.js

Backend

Postgres

Backend

Prisma ORM

Backend

LLM orchestration

AI / Machine Learning

pgvector

AI / Machine Learning

Whisper API

AI / Machine Learning

Google Analytics

Analytics & User Tracking

AppsFlyer

Analytics & User Tracking

FCM

Push Notifications & Messaging

APNs

Push Notifications & Messaging

Amazon S3

Storage & Authentication

AWS Cognito

Storage & Authentication

CDN

Storage & Authentication

RevenueCat

Payments & Subscription

Empowering organisations with data-driven insights

Contacts

UK

8 Devonshire Square, London, EC2M 4PL

BD

24/1 Mirpur Road, Level-10, Shyamoli Square, Shyamoli, Dhaka-1207

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