Swift Innovation — Prepared for Cliff Smith
Hair Visualization Project:
Where I Landed
The full brief from Charles to Cliff. Architecture, feature breakdown, cost model, compliance review, and competitive scan. Some of it is exciting and some of it is going to be annoying to read. You are getting both.
For Cliff Smith From Charles Brubaker August 2026 External-facing document
<45s
Four renders in under 45 seconds
$110K–$350K
Estimated range to launched product
4
Funded direct competitors now in market
Day 0
Consent architecture must be built first
01
What I understood you to want
Technology for women of color, hair first. Something like a Snapchat filter, but instead of a novelty, a real preview of what she would look like in a given style or after using a given product. Maybe makeup later. Maybe outfits. The core idea: show her how good she could look before she spends four to eight hours and a few hundred dollars finding out.
If I got any of that wrong, stop reading and correct me, because everything downstream is built on it.
02
What I would actually build
"She uploads a selfie, picks a style, and gets four renders of herself in it within about 45 seconds. She compares them, saves the ones she likes, shares one to get opinions, and sends her favorite to a stylist as a consultation reference."
Two things make it different from the filters that already exist:
Differentiator 01 — Face Lock
Her face is never regenerated
The system replaces only the hair region and puts her actual face back, pixel for pixel. Then it automatically checks that her skin tone did not shift, and throws the image away and retries if it did. Every generic AI hair app quietly lightens and "corrects" faces. Users notice. I have read the reviews. Women are saying, in plain language, that the app changed their face and the result did not look like them. Building the thing that does not do that is a real position.
Differentiator 02 — Feasibility Layer
The app tells her whether she can actually get the style
Not just what it looks like, but whether it works on her hair as it is today, whether it needs extensions, whether it needs a few months of growth, or whether it needs processing and what that costs her hair. That is what a good stylist tells her in the first two minutes of a consultation, and as far as I can find, nobody has built it. This may matter more than the render itself.
03
Three things I would push back on
The Snapchat framing is wrong for this market — and that is good news
Live AR filters handle braids, locs, and twists worst, because those are three-dimensional and high-detail. Still-image generation renders them far better. So the right build is faster, cheaper, and better suited to exactly the styles that matter here. We give up "instant" and get "actually looks like braids."
Going shorter has to wait
Adding hair to a photo is straightforward. Going from waist-length braids to a tapered cut means the computer has to invent a hairline, forehead, and ears it cannot see, and hairlines are personal in a way that makes getting it wrong genuinely harmful. This is Phase 3, not launch. Which is painful, because the big chop is where this product would help the most.
The product half was under-built. I have corrected it.
You said style and product. The original spec handled product barely at all. Showing what a curl cream or a color actually does on her texture is easier to build than styles, more honest as a claim, and probably where the brand money is. Product-effect rendering (E-16) is now a first-class engine mode in Rev D.
04
The part you will not enjoy
This space has funded competitors now
When we talked, I assumed nobody was serving this market. That was true a few years ago. It is not true today. Industry press three weeks ago called textured hair tech a gold rush.
Myavana
AI hair analysis for Black women, founded 2012. $5.9M raised led by Ulta's venture arm with Amazon. Integrated into Ulta e-commerce. 14-year head start on textured hair data.
Parfait
Selfie-driven wig customization. $5M seed from Upfront and Serena Williams' fund. Now licensing its AI to other hair brands — the same white-label path in this package.
Swivel Beauty
Already runs a marketplace matching women to stylists who specialize in natural textures, searchable by hair type.
HairHunt
General AI hairstyle app. Launched November 2025, reported 320,000+ users by April 2026. User reviews confirm face alteration at scale — the exact failure mode this package was designed against.
Here is the fair read. Nobody combines all of it. HairHunt has the visualization but changes faces. Myavana has the analysis and retail relationships but not visualization. Swivel has the stylists. Nobody has the feasibility piece at all. The position is not "we found an empty market." It is "the pieces exist and nothing is joined up." That is a normal and workable place to start from. It requires better execution rather than just being first.
There is a legal problem that is completely manageable and completely non-optional
Biometric Privacy Liability — Real Cases, Real Settlements
Charlotte Tilbury
$2.925M
Virtual try-on settlement
Kenvue (Neutrogena)
$4.7M
Facial-geometry skin tool
MAC Cosmetics
Proceeding
Case allowed to proceed June 2026
$1,000–$5,000 per person, no requirement that anyone was harmed. A pre-revenue MVP with 1,000 Illinois users is a theoretical seven-figure liability if the consent flow is wrong. Almost every one of those companies got caught for the same thing: a face-scanning tool with no proper consent screen and no published retention policy.
"Doing it right costs about a day of engineering and a conversation with a lawyer, at the beginning. There is no version where we add it in a later sprint."
It costs real money
Recommended tier (excl. engineering)
$87K–$224K
Seed corpus shoot ($57K–$129K), legal ($16K–$46K), insurance ($5K–$25K), compute and infrastructure ($1.5K–$6K).
Including engineering at ~$200/hr
$143K–$349K
280–623 agent-directed hours for MVP including partials. Structure determines whether this is cash or contributed value — which is exactly what D-01 has to settle.
Largest single line item
The corpus shoot
Not engineering. Photographing a proper library of styles on real women across the full range of hair types and skin tones, with everyone properly paid and released. $57K–$129K (recommended tier). This library is also the only thing a competitor cannot copy.
The thing that surprises people
Braiding time
A 50-style catalog cannot be shot in a two-day production. A knotless install is 4–8 hours. 50 styles is 200–400 stylist-hours. Plan for staged releases or a mixed catalog with wigs (fast install).
05
What I need from you
06
What I think
I think there is something here. I think the feasibility idea — telling her whether she can actually get the style rather than just showing it — is the strongest thing in the package and it came out of pressure-testing your original concept rather than replacing it.

I also think it is a bigger commitment than either of us framed it as on the phone, and that you should decide whether you want to build a company or build a product that partners with one of the companies already in this space. Both are legitimate. They are different lives.

Tell me where I am wrong and let's talk.
Charles Brubaker — Swift Innovation — August 2026