GlowCycle

Skin guidance that adapts to your cycle and climate

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Inspiration

So usually, a breakout rarely feels like an abstract skin concern. I've had it happen the morning before an important event, or like, after trying a new product, or just while standing in front of a mirror and wondering “What is happening to my skin, and what should I do next?”

For many people who menstruate (me included), this uncertainty is made worse by recurring cycle-related changes. A routine that felt fine last week may suddenly feel too harsh, too heavy, or ineffective. Climate adds another layer: heat and humidity can make skin feel oilier and more congested, while dry or cold environments can increase tightness and sensitivity. Living in a tropical region where it's a little chilly at a point and it's hot at another point makes it a pain to figure out what exactly my skin wants.

So I realized, the problem is not a lack of skincare products. It is a lack of context.

Existing skin tools can describe what is visible, but they usually stop at a score. Period trackers can track dates, but usually do not connect those dates to measurable changes in the user’s skin. Product catalogs contain thousands of options, but rarely help someone understand which choice makes sense for them today.

That inspired me to build GlowCycle; a skin decision assistant that connects the moment of a skin scan to an actionable next step.

GlowCycle uses YouCam Skin AI to help users understand visible concerns such as acne, oiliness, moisture, redness, and texture. It then adds personal context: cycle phase, climate, previous scans, and optional lifestyle log, to provide an explainable skincare routine and product shortlist.

The cycle is not treated as a diagnosis, and GlowCycle does not claim that every breakout is hormonal. Instead, it helps users notice their own patterns over time.

I wanted to move beyond an AI skin scanner that tells users what they have, toward an experience that helps them decide what to do next.

The opportunity also extends to retailers and skincare brands. A GlowCycle-style experience could act as a personalized consultation before checkout, helping customers find relevant products, reduce trial-and-error purchases, and return to measure whether their routine is working. Personalized skin analysis and product recommendations are already established use cases for Perfect Corp.’s technology in beauty and retail experiences.

What it does

GlowCycle is a cycle-aware and climate-aware skincare assistant powered by YouCam Skin AI.

  1. Analyzes the user’s skin: The user uploads a clear selfie. GlowCycle sends the image to the YouCam Skin Analysis API and presents a structured skin summary, including concerns such as acne, oiliness, moisture, redness, radiance, texture. The result is presented as an understandable snapshot rather than a medical diagnosis.

  2. Adds personal context After the scan, GlowCycle combines the YouCam result with the current menstrual cycle day, the estimated cycle phase, the user’s climate profile and previous skin scans. The app uses this context to help users understand whether a current change is part of a recurring personal pattern, not to make a definitive medical claim.

  3. Recommends a next step Instead of stopping at analysis, GlowCycle generates an actionable AM/PM routine. Users can be recommended to cleanse gently, prioritize barrier support or avoid introducing multiple new products at once. All this in context with what their skin and body says, as well as their environment.

  4. Helps users choose products GlowCycle maps routine steps to a curated product catalog. The goal is not to push the most products. The goal is to help the user choose a smaller, more relevant set of options.

For a retailer, the same flow could become an AI-powered consultation:

Scan → understand concern → receive routine → discover suitable products → track progress.

This connects YouCam’s analysis capability to a clear purchase decision.

  1. Tracks changes over time: Users can rescan their skin and compare results across cycle days, cycle phases, climate contexts, products used and journal entries.

Over time, GlowCycle can surface personal observations such as: "Your acne score has been higher during the late luteal phase in your last two cycles.”

This is an extension of the same experience: helping users feel more confident when they are making beauty decisions.

How we built it

GlowCycle is built as a lightweight React web application using a modular architecture so the experience can work for both direct consumers and future retail integrations. Technology stack

Frontend: React with Vite

Styling: Tailwind CSS

Authentication: Firebase Authentication

Database: Cloud Firestore

API communication: Native JavaScript fetch

Skin intelligence: YouCam Skin Analysis API

Challenges we ran into

GlowCycle is a research-first app, so translating research on menstrual-cycle skin changes and climate into useful, responsible recommendations was challenging. Because everyone’s skin responds differently, I had to avoid presenting cycle phases as a diagnosis and instead treat them as personal context.

I also had to normalize YouCam’s asynchronous skin-analysis results and OpenWeather data into consistent formats that the recommendation engine could use. Handling different response structures, missing fields, and building secure serverless proxies to hide API keys required a dedicated data-normalization layer.

Accomplishments that I'm proud of

'm proud of building a working prototype that turns YouCam Skin AI results into personalized, cycle-aware, and climate-aware skincare recommendations. I love how GlowCycle goes beyond displaying arbitrary skin scores by actually helping users understand what those results mean and decide what to do next. Most importantly, I'm really glad I built something I will constantly use for myself.

What I learned

I learned that building responsible AI experiences requires more than just integrating an API. I had to combine research, user context, data normalization, and explainable rules while being careful not to present skincare guidance as medical advice. I also learned a massive amount about designing around asynchronous AI workflows, handling external data, and building secure serverless routes.

What's next for GlowCycle

I plan to turn GlowCycle into a complete mobile and web app with stronger personalization, longer-term skin tracking, and broader product coverage. I also want to make it a smarter, and much more proper ML model, and I want to put in more data so it works for a wider variety of climates and bodies (women with diseases, people on hormones). I also want to refine and productionize the data pipeline so GlowCycle can power retail-facing experiences for skincare brands, pharmacies, and e-commerce stores, helping customers receive personalized guidance before making a purchase.

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