GlowBot

Inspiration

We use skincare every day, but most people don’t really know what’s inside their products or which ingredients might raise red flags. We wanted to create something that makes it easy for anyone to spot potentially harmful or irritating ingredients and understand how safe their products really are.

What it does

GlowBot lets users input any skincare product and instantly analyzes its ingredients based on EU cosmetic regulations. It flags ingredients that may be banned, restricted, or potentially harsh, giving users a quick, visual breakdown of what’s in their skincare products.

How we built it

We built GlowBot in Python using pandas for data processing and Tkinter for the user interface. Our logic reads multiple EU regulation annexes separately — each defining different categories like banned substances, restricted ingredients, preservatives, and colorants — and uses that information to assess each ingredient’s potential risk.

Challenges we ran into

One of the biggest challenges was figuring out how to calculate accurate risk scores across different annexes, each with its own purpose and structure. We also had to carefully handle the CSV files to ensure our program interpreted the data correctly without merging everything into one dataset.

Accomplishments that we're proud of

That we created something working.

What we learned

We learned a lot about how EU cosmetic regulations are structured, how to clean and interpret complex datasets, and how to transform technical data into something visual and understandable.

What's next for GlowBot

Next, we want to integrate an AI assistant that can explain why certain ingredients are restricted or should be used with caution. We also plan to add the ability to toggle between different countries’ regulations and keep GlowBot automatically updated as new products and regulatory changes come out.

Built With

• pandas
• python
• tkinter