PlateIt.
Good food, a college budget, and a simpler way to cook.
My role: defining the product concept, selecting the first features, and building an early prototype. The project is in the prototype stage; user testing and full image recognition are future work.
Why I created PlateIt
As a college student, I wanted to keep my food costs low while still making meals I enjoyed. That goal inspired me to create PlateIt: an app concept that helps turn food inspiration into something practical to cook at home.
I wanted a simpler way to go from seeing a good meal to understanding its ingredients and how to make it. PlateIt brings suggested recipes, cooking instructions, and ingredient alternatives into one experience, with the goal of helping students explore good food within their budget.
How could I make good food at home while keeping costs low?
One starting point, several useful answers
The prototype centers on a photo upload or camera input. From there, it presents a suggested dish and recipe instructions, estimated calories and protein, carbs, and fat. Saved recipe history helps someone return to an idea later.
Make it fit
Dietary filters help narrow the recipe experience. The current concept includes vegetarian, vegan, pescatarian, gluten-free, keto-friendly, lactose-free, kosher, and halal options. These are filters in the prototype, not a verified certification of every recipe.
Make it practical
An easy and fast recipes section gives people another route into the product when they do not have a photo. Ingredient alternatives give people flexibility to use what they already have or consider a more affordable option. Estimated macros add another way to decide whether a meal fits their needs. The prototype does not yet compare ingredient prices or calculate meal costs.
Why the first version is a prototype
Recognizing an arbitrary meal from a photo is a different challenge from designing a useful recipe journey. I chose to start with sample predictions so I could shape the experience around the output first: what should someone see, compare, save, and cook?
Start with the journey
Put photo input, recipe steps, macros, and preferences in one flow that can be explored and critiqued.
Show assumptions clearly
Food identification and macro values are sample or estimated outputs. The interface should communicate that uncertainty to users.
Validate before expanding
Find out whether people value the recipe experience and where they hesitate before investing in more complex recognition.
Test the usefulness, then refine
The next step is to ask fellow college students to try a simple task: upload a food photo and find a recipe they would consider making within their budget. I want to observe where they pause, whether the suggestion matches their expectations, and what information would help them trust the recipe and nutrition estimate.
I also want to learn whether the ingredient alternatives help students work with what they have, and what budget information would make the experience more useful. That feedback can guide one focused improvement to the flow. I would then evaluate whether people can reach a usable recipe, understand the estimate, and save or act on the result.
Current status: Prototype. This page describes product choices and proposed validation. It does not claim completed user research, accurate photo recognition, or measured product outcomes.