AI Meal Planner - Cuvio

Product Lead • Ongoing

Product Strategy UX Research Agile Development Growth Planning App Deployment Marketing Analytics

Project Overview

Cuvio is a SwiftUI-based meal planning app with a Node.js backend on AWS EC2, designed to generate personalized weekly meal plans, reduce food waste, and streamline grocery shopping. It removes decision fatigue while promoting sustainability.

Problem Statement

Meal planning is time-consuming and food waste is costly. Existing apps are often rigid, require excessive manual input, or fail to account for dietary restrictions. Users struggle to:

  • Generate meal plans that suit their budget, preferences, and household size.
  • Reduce ingredient waste while maintaining variety.
  • Automate grocery lists without repeated effort.

Solution

Cuvio solves these problems through:

  • Smart Meal Generation – Personalized weekly meal plans with controlled recipe repetition.
  • Automated Grocery Lists – Lists generated based on meal plans to reduce waste.
  • Flexible Scaling – Recipes adjust to household size and budget.
  • Seasonal & Dietary Awareness – Prioritizes seasonal produce and supports multiple dietary preferences.

Approach

  • User Research: Interviews and competitor analysis informed feature prioritization.
  • Design & Development: SwiftUI frontend with Node.js backend deployed on an AWS EC2 cluster.
  • Agile Execution: Solo development with iterative releases and user feedback cycles.
  • Marketing & Launch: Branding, keyword optimization, TikTok & Apple Ads campaigns.

Impact

  • Apple App Store Conversion Rate: 3.8%
  • TikTok Campaign Download CTR: 4.3% from 10K views
  • Early user feedback highlights the app’s automation, flexibility, and usability.

Key Learnings

  • Marketing & Targeting Matter Most – Keyword optimization, audience targeting, and ad campaigns drive adoption.
  • Deployment Skills are Crucial – Learned EC2 instance management, server deployment, and backend scaling.
  • User-Centric Product Strategy – Understanding target users informs features, engagement, and retention.

Technology Stack

  • Frontend: SwiftUI
  • Backend: Node.js
  • Deployment: AWS EC2
  • Analytics: PostHog

Future Plans

  • Launch Android version.
  • Introduce AI-driven recipe suggestions and personalized nutrition insights.
  • Expand features based on real-world user feedback and engagement metrics.
1.05%
Apple Search Ads TTR
6 months
Time Invested
0 → 1
Solo-Built App
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