EYEconic One request deck arrow_forward
pre-seed · 2026 · fashion AI

THE OPERATING
SYSTEM FOR GETTING DRESSED.

stop guessing. start dressing.

now available · ios & android
download on the App Store get it on Google Play
request deck arrow_forward how it works
$6B+
Fashion app market by 2027
67%
Style anxiety, daily
4-in-1
Chat · Vision · Wardrobe · Avatar
10K
18-month user target
01 / overview what we're building

an AI stylist
that actually sees
your closet.

need to look sharp tomorrow. nothing fits the way it used to. the closet is full but there's nothing to wear. sound familiar? you're not alone.

EYEconic One is an AI-native styling assistant for the way people actually get dressed. message Connie, your AI stylist and fashion friend, anytime. snap your closet into a digital wardrobe. try outfits on your avatar before you put them on. one decisive answer to the most repeated question of the day: what do i wear?

built mobile-first. privacy-first. taste-first.

decision fatigue ✦ ends here ✦ a stylist in your pocket ✦ closet, meet AI ✦ dress with confidence ✦
decision fatigue ✦ ends here ✦ a stylist in your pocket ✦ closet, meet AI ✦ dress with confidence ✦
02 / the problem why now

getting dressed is the most repeated
decision no one has solved.

67%
of adults report regular anxiety about dressing for an occasion.
YouGov · 2024
$460
spent annually per person on clothing worn fewer than five times.
ThredUp resale report
20%
of the average wardrobe is in actual rotation. eighty percent sits idle.
Cambridge / IFM

think bigger.
dress sharper.

big ideas are only as good as your ability to execute them. it's why we invest in technology that delivers, not just talks. it's why the wardrobe stays on your phone. it's why every screen has an opinion. world-class styling, in the palm of your hand.

03 / the stack four layers, one stylist

the complete style stack.

full-stack styling means you're not relying on one app for outfits, another for storage, and a chatbot for advice. we built a team, and a system, that does all three.

chat_bubble

message Connie.

your fashion friend in your pocket. text her about weddings, work pitches, first dates, sunday errands. ask anything. get a real answer, in plain language.

your stylist →
visibility

computer vision

snap any garment. category, color, fabric, formality, season. classified in under a second.

layer 02 →
checkroom

wardrobe graph

your closet, but as a graph. items have relationships. every wear sharpens the model.

layer 03 →
face_retouching_natural

virtual try-on.

your avatar wears the fit before you do. spin it. swap pieces. test combinations without changing twice. see how it actually looks on you. not a model.

your avatar →
auto_awesome

occasion intelligence

smart casual for dinner. business sharp for a pitch. weather-aware. context as a first-class citizen.

module →
recommend

outfit memory

log a fit with one tap. the model learns what you actually wear vs. what you said you would.

module →
shopping_bag

pre-purchase fit-check

about to buy something? we tell you whether it goes with what you already own. before you tap pay.

module →
lock

privacy by default

closets are intimate. on-device storage by default. you opt in to anything that leaves the phone.

module →
tune

taste calibration

first-week onboarding tunes Connie to your aesthetic, minimalist, classic, expressive, downtown, without a quiz that takes thirty minutes.

module →
04 / proof milestones in the open

results that
speak for themselves.

milestone 01 01

250 beta users in NYC, validated.

tight cohort. design-conscious. retention curves are tracking ahead of category benchmarks.

case detail →
milestone 02 02

vision pipeline, sub-second on-device.

classification accuracy on real-world closet shots crosses 92% with privacy-preserving local inference.

case detail →
milestone 03 03

Connie v1. closet-aware reasoning.

conversation grounded in the user's real wardrobe, not a generic style chatbot. tested across 12 dress codes.

case detail →

ready to
back the round?

we're closing a $400K pre-seed (with a $740K ceiling) to ship the first version of EYEconic One on ios. partners who can compound capability, design, AI, fashion, consumer mobile, get priority.

request deck arrow_forward
product · iOS · in build · Q3 2026

four layers. one stylist.

message Connie. snap your closet. try it on your avatar. wear it. each layer makes the others sharper.

layer 01 chat_bubble
01 / Connie

your fashion friend, in your pocket.

meet Connie, your AI stylist. message her like you'd text a stylish friend. send a screenshot from the fitting room. ask the question you'd normally save for the one friend with taste.

weddings, work pitches, first dates, parents-in-law, beach weeks, funerals, sunday brunch. any situation. any time. no judgement.

  • check_circletext-based chat, available the moment you need her
  • check_circlewarm, conversational tone, not a chatbot
  • check_circlehonest pushback when an outfit isn't working
  • check_circleremembers your taste, your closet, your week
layer 02 visibility
02 / vision

build a digital closet in minutes.

snap a garment on a hanger, on the floor, or still in the bag. the vision model classifies category, color palette, fabric, formality, and seasonality. the wardrobe builds itself as the user dresses. and as they shop.

  • check_circlesub-second classification, on-device where possible
  • check_circlereceipt and product-page parsing for new purchases
  • check_circlebackground segmentation tuned for clothing
  • check_circleprivacy-first: photos stay local by default
layer 03 checkroom
03 / wardrobe

outfits that fit your life.

the wardrobe is a graph, not a list. items have relationships: this jacket pairs with these three pants, in these contexts, in this weather. every wear, skip, or repeat sharpens the recommendation.

  • check_circleone-tap outfit logging
  • check_circlewear-frequency analytics, what's earning closet space
  • check_circlepre-purchase fit-check against existing wardrobe
  • check_circleweather aware
layer 04 face_retouching_natural
04 / avatar

see it on you, before it's on you.

build a personal avatar, your proportions, your features, your everyday, and use it as a fitting room. drag any piece from your closet onto your avatar. swap. spin. layer. screenshot the looks you love.

no more changing four times before you find the one. no more guessing whether the new shirt actually works with the trousers. try it on the avatar first.

  • check_circlepersonal avatar, built from a few photos, kept private
  • check_circlemix items from your closet with anything you're considering buying
  • check_circlesave and share looks with Connie or a trusted friend
roadmap plan to ten thousand mornings

what's next,
in plain sight.

Q2 2026
closed beta · 250 users
tight cohort of design-conscious early users in NYC and SF. validate retention and styling-prompt depth.
Q3 2026
public iOS launch
app store release with onboarding flow, wardrobe import, and Connie v1. targeted PR + creator seeding.
Q4 2026
10k active users
outfit social layer launches. first paid tier introduced for power users. data flywheel begins compounding.
2027
series a readiness
brand and retail partner integrations. web companion. clear retention curves and unit economics for the next round.

see it
in action.

request access to the closed beta, or grab the deck and the working build of the iOS app.

investor materials arrow_forward
team · founder & co-founder · NYC · hiring soon

product vision
meets technical excellence.

Jake Hyman, founder and CEO of EYEconic One
CEO
founder · chief executive

Jake Hyman.

Jake leads EYEconic One's product vision, brand, and go-to-market. he spent his early career obsessed with the gap between how people say they shop and how they actually get dressed: the gap this company exists to close.

he's the founder you meet first. runs investor relations, the brand voice, and the user research that shapes every screen of the app.

product strategy brand fundraising go-to-market
Parth Kulkarni, co-founder and CTO of EYEconic One
CTO
co-founder · chief technology officer

Parth Kulkarni.

Parth owns the technical architecture: the vision pipeline, the wardrobe graph, and the conversational layer that ties them together. he's been building production ML systems since before "AI" was a category investors had a thesis for.

treats latency like a design problem and privacy like a non-negotiable. the closet stays on your device because he insists.

ML / vision mobile architecture infrastructure privacy engineering
how we work operating principles

small team.
big convictions.

rocket_launch

ship the smallest useful thing.

the fastest way to learn what customers actually want is to put a working version in their hands. we bias toward shipping over planning, every week.

style

taste is a discipline.

we treat product taste the way other companies treat ops. something you study, debate, and iterate on. every screen has an opinion.

lock

privacy is a feature.

the wardrobe is intimate data. we architect for on-device storage by default and revisit only when a user asks us to.

groups

full-stack, in-house.

brand, business, AI, engineering, covered without the meeting tax. the founders ship the product, talk to the users, and own the outcome.

bolt

latency is a design problem.

if it takes five seconds to get an answer about an outfit, the user will guess instead. speed is non-negotiable.

handshake

customers, not users.

we say customers on purpose. the goal isn't engagement. it's that someone gets dressed and goes about their day, faster.

careers we're hiring soon

want to
build with us?

careers support@eyeconicone.org → press & general support@eyeconicone.org → founder · Jake Hyman jakehyman@eyeconicone.org →
open round · pre-seed · closing Q3 2026

back the company that
makes the closet actually useful.

EYEconic One is the AI-native styling assistant for the next decade of getting dressed. raising a small, focused round to launch on iOS and prove the wardrobe graph at scale.

the ask
$400K
raising $400K · ceiling $740K

pre-seed round. SAFE on a friendly cap, with a $740K hard ceiling. we're optimizing for partners who can compound capability, design, AI, fashion, consumer mobile, alongside the dollars.

request the deck

here's what's inside.

full go-to-market, vision-pipeline architecture, retention model, financial projections through 2028, and a working build of the iOS app. we'll send the deck after a quick read of who you are.

use of funds $400K floor · 18 months

where the
money goes.

50%
$200K
core app development & engineering. ios build, wardrobe-graph backend, vision pipeline, infrastructure.
25%
$100K
AI/ML enhancements & Connie features. conversational layer, taste calibration, on-device inference, classification quality.
15%
$60K
operations & team growth. first hires, infrastructure, legal, runway buffer.
10%
$40K
organic user growth & community. creator partnerships, content engine, beta cohort, brand moments.
milestones the path to series a

first ten thousand
mornings.

now → Q2 2026
closed beta · 250 users
tight cohort of design-conscious early users in NYC and SF. goal: validate retention and styling-prompt depth.
Q3 2026
public iOS launch
app store release with onboarding flow, wardrobe import, and Connie v1. targeted PR + creator seeding.
Q4 2026
10k active users
outfit social layer launches. first paid tier introduced for power users. data flywheel begins compounding.
2027
series a readiness
brand & retail partner integrations. web companion. clear retention curves and unit economics for the next round.
contact talk to us directly

speak to us
directly.

investor inquiries invest@eyeconicone.org → founder · Jake Hyman jakehyman@eyeconicone.org → press & general support@eyeconicone.org →