Formelle

We were inspired by how overwhelming and confusing skincare ingredient labels can be. Many people, especially women, want to make informed, safe, and sustainable choices for their skin, but ingredient lists often look like chemistry exams. We wanted to bridge the gap between science and everyday understanding by creating a tool that makes ingredient transparency simple, educational, and personal. Formelle is a personalized ingredient analysis platform that helps users decode skincare product labels. By inputting ingredients or entire lists, users receive clear, science-based insights about each chemical’s origin, safety, environmental impact, and relevance to specific concerns such as acne, sensitivity, pregnancy safety, and eco-friendliness.

We built the project using Flask (Python) for the backend and Tailwind CSS + HTML for a modern, elegant frontend. Our data is structured in a single JSON file (data.json) that contains detailed information about each chemical including its description, source, human health impact, environmental safety, and fragrance or pregnancy safety indicators. The backend processes user inputs and matches them against this dataset, dynamically generating personalized ingredient insights based on the user’s selections and product entries.

Some of the challenges we faced while conducting our project were, structuring chemical data in an efficient and readable format, connecting the backend and frontend smoothly through Flask routes, designing a clean and professional interface under time pressure and ensuring our database logic returned accurate and meaningful results for each ingredient. However, beyond these challenges we accomplished many things. We created a functional and intuitive prototype in less than 24 hours, built a fully working backend system with real ingredient data, designed a cohesive brand identity and UI that feels both scientific and approachable and laid the groundwork for future AI-powered ingredient parsing and scoring.

We learned how to integrate data-driven logic into a user-focused design, balance aesthetics with functionality, and collaborate efficiently across different skill sets. We also deepened our understanding of web development and the importance of clean, transparent data presentation. As for our future progressions with our project idea, we plan to integrate AI models to automatically extract ingredients from messy product labels, provide personalized risk scores, and recommend cleaner alternatives. In the long term, we envision Formelle expanding into a browser extension or mobile app, empowering consumers to make informed, confident choices, anytime, anywhere.