Create a gallery and share it, instantly.

Gallify was an AI-powered iOS marketplace for digital art, with AR viewing. Digital artists could put up a gallery in a few minutes, and collectors could hang the work on their own wall in AR before buying it. Edward Profio joined early, became Chief Product Officer and a co-founder, and ran product and engineering through 2021, when the team took what it had built into public art with CODAworx.

Shipped and Scaled · 2016–2021

See the product Case study ↗

Product · 2016–2021 Digital art · Marketplace iOS · ARKit · Polygon Led to CODAmarket, 2021

Gallify

Discover, see it on your wall, bid, and share a gallery.

7,500+: users: 2,500+ artists and 5,000+ buyers
~15%: growth month over month, mostly organic
+30%: click-through from recommendations
+20%: average order value

−60%: time to list a piece, from auto-tagging
+25%: search conversion, from auto-tagging
60→85%: on-time delivery
3+: major releases over five years

Recommender lifts were measured against the previous feed ordering, on click-through and average order value rather than time in the app. In 2021 the team carried the work into public art with CODAworx, which became CODAmarket.

[ 01 ] // Overview

A next generation gallery
for the digital age

Gallify started as a small AI-focused team. Edward joined early and became Chief Product Officer and a co-founder. Over five years he led product, ran engineering through a lot of hiring, and in 2021 led the team’s move into public art with CODAworx.

Digital artists had nowhere to show and sell their work that felt like a gallery. Collectors couldn’t see a piece in their own space, and couldn’t prove they owned it. So the team built an iOS app with galleries you could create and share in minutes, AR to see any piece on your wall at its real size, and ownership recorded on a blockchain.

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RoleChief Product Officer and co-founder
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Team10+ people in 4 sub-teams
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StackiOS, ARKit, Object Capture, Solidity on Polygon
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When2016 to 2021

[ 02 ] // The problem and who had it

Digital art had nowhere
that felt like a gallery

Back then digital art mostly lived on social feeds built for photos. Artists could post, but there was no place that treated a piece of digital work with the presence a gallery gives a painting.

Artists: no gallery

Digital artists had nowhere to show and sell their work that felt like a gallery, and every artist wanted to be seen.

Collectors: no sense of the room

They couldn’t tell how a piece would look at home, which is how most people decide to buy art.

Collectors: no proof of ownership

They had no reliable way to prove they owned what they bought.

The bet. Seeing a piece on your own wall and being able to verify you owned it would make digital art feel like it counted, and good discovery would help collectors find work they’d never have searched for.

Flows before screens. Edward sketched sign-up, the library, playlists and search by hand and argued over the paths with the team until they agreed on them. Only then did the team move to high-fidelity iOS designs, and after that to a beta landing page with a Discord community for early feedback.

The sketches cover what mattered at the start: how an artist creates a gallery, how a collector builds a library of favourites, and how playlists let people share taste. A few of those ideas survived and a lot of them didn’t. Starting on paper meant changing course cost nothing.

The beta page said “Create a gallery and share, instantly,” and the team used that sentence to test every feature. Did it make the first gallery faster to create, or easier to share?

[ 03 ] // What was built

Galleries in minutes,
art on your own wall

Three major releases over five years: the iOS app itself, the AR gallery experience and marketplace transactions on the blockchain. The platform was designed, built and launched ahead of schedule.

The app, end to end

Discover, place it on the wall, publish a gallery

Collectors pick a few styles and get a first feed built from them. Any piece can be placed on a wall in AR at its real size, resized, photographed and bid on from the same screen. Artists add works, mint each as a one-of-one and share a gallery link.

Collector setup and discovery: pick a few styles, get a first feed built from them, then tap “Why?” to see and adjust what a pick is based on.

AR in a real room: walk around, place the piece on the wall at its real size, resize it, take a snapshot, then bid from the same screen.

The artist side: add works, mint each as 1 of 1, publish a gallery and share its link.

Galleries and listings

A gallery for every artist, a live auction for every piece

Each artist gets a gallery and a link to share it. Publishing from a phone takes minutes: upload images or capture a 3D piece, mint the work as a one-of-one, and share one link. Each listing shows live bidding and verified ownership, and collectors hear about it while the auction is still running.

An artist's gallery page with works, collectors, followers and a share button — Each artist gets a gallery and a link to share it.

A listing with a live auction, current bid, verified ownership and bid history — A listing with live bidding and verified ownership.

A lock-screen alert that the collector has been outbid, with time left in the auction — An outbid alert while the auction is still running.

AR and ownership

See it at home, then own it verifiably

Built on Apple’s ARKit, so collectors could place a piece on their own wall at real size before bidding. Object Capture later let artists scan physical sculptures into 3D and show those in AR too. Purchases are tokens on Polygon, an ERC-721 contract written in Solidity, with wallet connect, so a purchase meant verifiable ownership. Bids and purchases are approved in the collector’s own wallet.

Polygon’s low fees and fast confirmation suited small first purchases by new collectors
Gallify never held anyone’s keys

A framed piece hanging above a bed in AR at its real size, with size options and a bid button — AR in a bedroom: the piece hangs above the bed at its real size.

Connecting a Polygon wallet before the first bid.

Placing a bid, approved in the collector's own wallet — A bid, approved in the collector’s own wallet.

[ 04 ] // How AI was used, and how it was measured

The right piece
in front of the right person

Collectors arrived without a clear idea of what they wanted, and every artist wanted to be seen, so a feed that put the right piece in front of the right person was the most valuable thing the team could build. Edward led the AI recommender for listings.

The recommender

Every pick says why

It ranked live auctions and listings for each collector from their browsing behavior (what they had viewed, saved, bid on and bought) and from how visually similar pieces were, plus each piece’s style, medium and artist. New collectors picked a few styles they liked first, so the feed wasn’t empty on day one.

Each pick had a reason behind it, such as works you saved or pieces you bid on, and controls to see more, see less, hide that artist or manage personalization. Picks used only a collector’s own activity on Gallify.

The ranker reorders listings as the collector browses
What collectors did with the controls fed back into the ranking

Tapping Why? shows what a pick was based on, with controls to see more, see less or hide an artist — Tapping “Why?” shows what a pick was based on and lets the collector adjust it.

AI feature	What it did	How it was measured	Result
Recommender	Ranked a feed of live auctions and listings for every collector from visual similarity and browsing behavior	Against the previous feed ordering, on click-through rather than time in the app	+30%
Recommender	Same feed, same comparison	Average order value	+20%
Auto-tagging	Computer vision tagged 2D and AR/VR artwork, so artists no longer tagged every piece by hand	Time to list a piece	−60%
Auto-tagging	Tags fed search across the listings	Search conversion	+25%

[ 05 ] // Architecture

Upload, tag, rank,
and learn from every bid

Artists upload, computer vision tags each piece, and the recommender ranks a feed for every collector.

How Gallify worked

Artists upload 2D or AR/VR work, auto-tagging files it into the listings, the recommender ranks each collector’s feed, and views, saves, bids and buys feed back in.

Layer	What it did
iOS app	Auctions, discovery, galleries and profiles, built in Swift for iPhone
AR layer	ARKit places any piece on a wall at real size; Object Capture turns physical work into 3D
Ownership	Solidity smart contracts on Polygon issue each piece as a one-of-one token
Wallet	The collector approves every bid and purchase in their own wallet
Signals	What a collector views, saves, bids on and buys; how visually similar pieces are; each piece’s style, medium and artist
Feedback	What collectors did with the controls, and the measured results on click-through and average order value

[ 06 ] // Product decisions and trade-offs

Six decisions,
two honest trade-offs

Discovery over search

Collectors rarely know what to search for, so the home screen is a per-collector feed with local auctions by city, curated playlists and a featured room, instead of a search bar.

AR as the differentiator

Built on Apple’s ARKit so collectors could place a piece on their own wall at real size before bidding. Object Capture came later, so artists could scan physical sculptures into 3D.

Ownership on a blockchain

Purchases are tokens on Polygon with wallet connect, so a purchase meant verifiable ownership. Low fees and fast confirmation suited small first purchases.

Collectors keep their own keys

Bids and purchases are approved in the collector’s own wallet. Gallify never holds anyone’s keys, which meant fewer security obligations and more trust.

Lower the bar for artists

Publishing a gallery from a phone takes minutes: upload images or capture a 3D piece, mint the work as a one-of-one, and share one link.

Measure sales, not screen time

The feed was judged on click-through and average order value against the previous ordering, not on time in the app.

Trade-off: AR

It was the feature people remembered, and nothing else felt like the product. It was also a big engineering investment that only paid off if enough collectors cared about seeing a piece in their room. People loved the moment. The team never got clear evidence that it made them buy.

Trade-off: blockchain

On-chain ownership solved the real problem of proving a piece is yours. It also added friction: new collectors had to set up a wallet before they could bid, before they’d seen a single piece they loved. Fees stayed low on Polygon and the wallet step was made as clear as possible, but it still cost growth.

[ 07 ] // Results

Shipped,
and scaled

Gallify grew to more than 7,500 users at about 15% a month, mostly organically. People used the AR view, the recommendations measurably moved sales, and the user base kept growing.

Outcome	Result
Users	7,500+: 2,500+ artists and 5,000+ buyers
Growth	About 15% month over month, mostly organic
Click-through from recommendations	+30%
Average order value	+20%
Time to list a piece (auto-tagging)	−60%
Search conversion (auto-tagging)	+25%
Major releases	3+: marketplace transactions, AR galleries, iOS
Platform	Designed, built and launched ahead of schedule
Business	In 2021 the team broadened from digital art to public art with CODAworx, which became CODAmarket

[ 08 ] // Team and delivery

Six projects, four sub-teams,
10+ people

By the busiest period Gallify had six projects running across four sub-teams. Edward was Scrum Master and the main technical decision-maker, setting product priorities and engineering standards. Delivery was unreliable when he took it on. Here is what changed.

Rhythm

Regular sprints and one-on-ones, so problems surfaced in a week instead of at the deadline.

Standards

Written engineering standards, including what “done” meant, so quality didn’t depend on who was reviewing.

Hiring

Edward ran the whole process, from sourcing to onboarding, as the team grew from 3 to 10+.

Onboarding

The codebase and the way the team worked were documented, so new engineers could contribute sooner.

Delivery measure	Result
On-time delivery	From about 60% to 85%
Average bug resolution time	About 35% faster
Team velocity	About 30% higher, with scope and budget within 10% of plan
Time to productivity for new engineers	About 25% shorter
Active projects	All 6 delivered on schedule, within 8% of estimates on average; production incidents under 2% of deployments

[ 09 ] // 2016–2021

From first sketch
to the next venture

2016
Joins the early team
Edward joins a small AI-focused team and becomes Chief Product Officer and a co-founder.
2016–2021
Flows, then screens, then a beta
Hand-drawn flows, high-fidelity iOS designs, then a beta landing page with a Discord community for early feedback.
2016–2021
Three major releases
The iOS app itself, the AR gallery experience and marketplace transactions on the blockchain, with the recommender and auto-tagging on top.
2016–2021
7,500+ users
2,500+ artists and 5,000+ buyers, growing about 15% a month, mostly organically, as the team grew from 3 to 10+.
2021
On to public art
The team broadened from digital art to public art, which became a new venture with CODAworx: CODAmarket. The app’s code was made public so the work could still be seen.

[ 10 ] // The next chapter, and Edward’s role

The product worked.
The bigger market was elsewhere.

In 2021 the team broadened from digital art to public art, which became a new venture with CODAworx: CODAmarket. Edward recommended the move, and carried it through with care for the people, the code and the commitments.

Before deciding he looked at four things: whether the people who tried Gallify came back, whether new collectors kept arriving without a push, whether Gallify could afford another year of the same bet, and whether the team was still excited about it. Weighing those against the larger market in public art that the CODAworx partnership had opened up, he recommended putting the team’s effort there.

He told the team directly, did what he could for the people who had put years into it, and made the app’s code public so the work could still be seen.

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ProductSet product priorities, led the recommender, and took the platform from hand-drawn flows to a launched iOS app
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EngineeringScrum Master and main technical decision-maker across six projects and four sub-teams
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TeamRan hiring from sourcing to onboarding as the team grew from 3 to 10+
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The callRecommended taking the team and what it had built into public art

What carried forward

Test demand first

Gallify built AR and blockchain ownership ahead of the market. What carried forward: test demand with something much cheaper first, such as a landing page, a handful of artists and a manual version of the experience.

Pick the retention number up front

Delivery numbers improved a lot. The number that decides a business is retention, so decide in advance which retention number justifies continuing, and look at it every month.

Follow the bigger market

Moving to the bigger market was the right decision, and it is the one that led to CODAmarket.

Explain every pick from day one

Telling users why a piece is shown, and letting them change it, was cheap to build and gave a clearer signal than clicks alone.

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Gallify is an Aurifex product from Shipped and Scaled: earlier work that shipped to real users and scaled. Every Aurifex product is held to the same gold standard for AI in skilled work.