PlastIQ

You can barely go a day without hearing about how detrimental to your health microplastics are, and how they are contaminating our entire food supply. This posed an interesting opportunity to put a spin on all the photo-based calorie counting apps that had hit the app store in recent months. The goal was straightforward: could I create an app from scratch using AI tools, market it, and receive paying customers?

The app is built natively for iOS using SwiftUI and relies on Supabase for the backend infrastructure—user authentication, data storage, and subscription management. The core intelligence comes from OpenAI's image recognition API, which processes user photos against a carefully crafted prompt to generate the microplastic risk score. The tailored prompt instructs ChatGPT4o to analyze food and grocery images to estimate microplastic exposure based on packaging, commonly known food contaminants, serving method, and several other factors. ChatGPT is instructed to return a specifically structured JSON payload that breaks down the estimated microplastic exposure on a 0-100 score, for each ingredient identified in the image. That payload is then used to build a table, splitting out the individual score for every ingredient and component of the meal. The app will then creates a composite score, weighing the values for ingredients that are more present in the meal.

At this point in time PlastIQ has 2 paying customers, netting a generous $9.99 Monthly Recurring Revenue. I have debated on whether or not to move forward with a proper marketing plan for this app. Either way, I am considering this a success for my first attempt into the consumer SaaS world.

This project guided me through Mobile App Development (a new venture for me), App Store regulations and review processes, standing up my own backend platforms with Supabase, and exploring AI-powered marketing tools. The learning curve was steep but rewarding—proving that with modern AI tooling, shipping a functional product is more accessible than ever.