Naee

Naee helps people check out hairstyles before actually getting one. It helps you talk through and decide which haircut would look best on you. Imagine bald people seeing a hairstyle, that's powerful.

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Inspiration

When I was a kid, I got a haircut so spectacularly wrong that I walked home with my hands glued to my head, not sure whether I had failed to explain what I wanted or whether the barber simply had a vision of his own, and that tiny, embarrassed walk home became a fleeting memory that still pops up whenever I think about how risky hair decisions can feel. Most people are understandably wary of trying a new barber because instructions are interpreted differently, and a visual overhaul like changing length or color is a big decision that can be time consuming, irreversible, and expensive if it goes wrong, which is exactly why I built Naee.

Naee is not only for people hunting for a fix, because it is also for the curious and the playful, the ones who want to experiment and see how a Justin Bieber fringe or a Pedro Pascal wave might sit on their own face before they ever sit in a chair.

What it does

Naee has three modes: Try New Hairstyle, Stylist Mode, and Copy Hairstyle, and each one is designed to remove friction while giving me and my users instant, confidence-building feedback.

Try New Hairstyle

I keep the idea simple by offering multiple hairstyle options tailored to face shape, and the illustrations adapt based on face shape and gender so the guidance always feels personal. I can select a look, tap generate, and I am done, or I can describe the exact style I want and watch it come to life with a realistic preview that feels immediate and specific. On the results screen I get a before and after slider that makes comparisons effortless, and I also get an auto-generated video that is ready to share on TikTok or Instagram so there is a fun, social moment built in.

Stylist Mode

Stylist Mode is my supercharged AI that hooks into the app’s internal system after onboarding has already detected face shape, so I can talk naturally about what I want and get recommendations that fit my features while also seeing instant previews that match those suggestions. If I do not love the first take I simply ask Naee to make the hair longer or tweak the volume or adjust the fringe, and it updates the preview automatically so iteration feels like a conversation rather than a chore.

Copy Hairstyles

Copy Hairstyles is straightforward and very fun because I can drop in anyone’s hairstyle and Naee will adapt the look to my hair texture, and to reduce friction for first-time users I also included a set of popular presets so people can start with a single tap. The result screen again includes a before and after comparison along with quick actions to save the image and generate a slider video for content, which keeps the experience fast and satisfying.

How I built it

I am a solo developer and this is the third app I built during Ship-a-thon, and I kicked it off around August 20 by refining prompts and evaluating models for the different tasks before sketching wireframes for all the core screens that would make the experience coherent from the first tap. I planned the architecture to handle spikes gracefully because viral moments are both a hope and a stress test, and then I went heads-down for a focused twenty-day sprint to develop the app end to end.

Stack Used

  1. SwiftUI

  2. Firebase Functions

  3. CoreData

  4. Python

That is it, lean and effective.

Challenges I ran into

Launch day surprised me with a bug that acted like a hard paywall due to how DeviceCheck identifies new users for trials, yet despite that hiccup the launch was still successful and the app made about 150 dollars in the first three days with zero promotion, which validated the problem and the appetite for this solution. I was also asked by App Review to support iPadOS even though I had not enabled it, which meant I had to redesign views with responsive layouts to cover all size classes, and while that was unexpected it ultimately made the product more robust across devices.

Accomplishments I am proud of

App adapts to gender

Right after the splash, I ask for gender to tailor suggestions, and that signal flows through the entire app so UI, recommendations, and even tone feel appropriate, and I maintain dedicated RevenueCat paywalls for women and for men so the funnel and messaging are precise.

App adapts to face shape

During onboarding I ask for a guided photo with simple constraints so processing is reliable, and from that single image I determine face shape and use it to personalize recommendations everywhere that matters.

Onboarding flow

I spent a lot of time making onboarding short, engaging, and instantly valuable, so the flow asks for age group and gender, then captures the photo that powers all features, and immediately shows the detected face shape with a set of recommended hairstyles so the first dopamine hit arrives in seconds rather than minutes.

Privacy first, no login required

I combine anonymous user IDs, Keychain, and DeviceCheck to grant trials and manage access without forcing logins, and I only collect usage data that helps improve the experience while keeping processing local where possible, with any data sent to fal.ai deleted within 24 hours so privacy is a feature, not a footnote.

Works across all iPhones and iPad

I tested from iPhone SE through the latest simulators and ensured everything scales cleanly, and because iPad renders with SE resolution at 2x the app also runs well there, which helps me assess demand on iPad without compromising the phone-first experience.

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