Vibha Polkam

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Vibha Polkam

Magic Tools

My Role

Sole Product Designer

Scope

0-1 Product Design

Tools

Figma, Jitter, Adobe

Platform

iOS, Android, Web

year

2022-2025

The Problem

Why we needed magic studio?

The entrepreneur photographing her own products on a bedsheet. The photographer who needed 40 background removals done before sunrise. The creator who knew exactly what she wanted but had no way to make it. They had no design background, no $600/year subscription, and no time to watch tutorials. The tools that existed were built for people who weren't them.

I was looking for the interaction patterns that created trust, and the ones that destroyed it. Four areas defined my research: object selection and spatial control, undo/redo logic and hierarchy, loading and processing states, and the final result moment.

The Solution

What we did to get there

Magic Studio was our attempt to build Photoshop for the people Adobe forgot. We wanted to give our users the control and freedom of their desired outcome. 150 million images later, here's what we actually learned about what that takes.

I was looking for the interaction patterns that created trust, and the ones that destroyed it. Four areas defined my research: object selection and spatial control, undo/redo logic and hierarchy, loading and processing states, and the final result moment.

Understanding the arena

Meet Rayna; and the Wall She Kept Hitting

  • She makes silver jewelery by hand and sells on Instagram & Etsy. Every product photo is shot on her kitchen table, white cardboard, phone camera, window light.

  • Every time a new batch was ready, the photos were the hardest thing, and the tools she tried made it worse.

And The Tools She Tried

  • Photoshop: Opened & watched a 40-minute tutorial, closed it and didn't go back

  • Lightroom: Made the wrong photo slightly prettier, but couldn't touch the background

  • Canva: Finally felt approachable, but pushed her toward a visual language that wasn't hers

  • Snapseed/VSCO: Not very easy-to-use UI

  • remove.bg: One job, zero friction. The whole product thesis in one reference.

  • Photoshop: Opened & watched a 40-minute tutorial, closed it and didn't go back

  • Lightroom: Made the wrong photo slightly prettier, but couldn't touch the background

  • Canva: Finally felt approachable, but pushed her toward a visual language that wasn't hers

  • Snapseed/VSCO: Not very easy-to-use UI

  • remove.bg: One job, zero friction. The whole product thesis in one reference.

0M+

Total Users (Current)

0M+

Images

Processed

0K+

Revenue

Generated

0%

Faster

Edits

0+

Videos Delivered

0+

Creators Served

0M+

Total Views

Real Testimonials from google play

What impact Magic Studio had on people

All reviews ▸

  • "So easy to use. I removed a whole crowd from my photo in literally two taps. I've tried Photoshop for years and never got results this clean this fast."

    Emily Carter

  • "The before/after button is genius. I use it every single time I edit. It gives me confidence that the AI actually did what I wanted before I save anything."

    James Richardson

  • "I run a small online store and used to pay someone to edit product photos. Now I do it myself in minutes. The background remover is incredible for product shots."

    Sophie Williams

  • "Faster than anything else I've used. The magic eraser works first try almost every time — I don't know how they made the AI this accurate on a phone app."

    Daniel Foster

  • "Very helpful for me as its good for removing unwanted objects from images."

    Charlotte Harris

  • "It's Perfect for all. You can use this for your business advertisements."

    a woman in a pink dress posing for a picture

    Rachel Smith

Critical Reviews & their possible solutions

"Doesn't let you do much without paying. Removing background is pretty much it for free users."

Plumbing's team is reliable and courteous, resolving our plumbing issues promptly and with meticulous attention to detail.

— Melissa W., Play Store, Feb 2026

Rachel Smith

Free Tier Discoverability

Free Tier Discoverability

Free tier complaints are a discoverability problem, users haven't found what's already available and onboarding and zero state can close that gap before they ever hit a paywall.

Plumbing's team is reliable and courteous, resolving our plumbing issues promptly and with meticulous attention to detail.

"The login situation at the beginning doesn't feel right… clicking links inside frames before I even see the app."

Plumbing's team is reliable and courteous, resolving our plumbing issues promptly and with meticulous attention to detail.

— Tina, Play Store, Dec 2024

Rachel Smith

Login Timing

Login-before-editing was a deliberate tradeoff for personalisation and sync, but reviews signal it needs to move to after the first aha moment, when users already have a reason to stay.

Plumbing's team is reliable and courteous, resolving our plumbing issues promptly and with meticulous attention to detail.

"Subscription billing confusion, charges after cancelled trials."

Plumbing's team is reliable and courteous, resolving our plumbing issues promptly and with meticulous attention to detail.

— Generic Reviews

Rachel Smith

Subscription Transparency

Surprise charges are a design failure when the commitment isn't made obvious at the point of decision, billing confusion is the inevitable result, and the subscription UI needs a dedicated pass for clarity.

Plumbing's team is reliable and courteous, resolving our plumbing issues promptly and with meticulous attention to detail.

“Magic Studio is popular around the world, with every image edited we put more power in the hands of the people. ”

magicstudio.com

THE BIG QUESTION

Magic Eraser: Would a non-designer feel confident using to use this under 60 seconds?

The first product was Magic Eraser: remove unwanted objects from any photo. No account required. No settings. No expertise assumed.

Before making a single wireframe, I audited the landscape, not to copy it, but to understand exactly where every existing product broke down. I studied 12+ apps hands-on: Photoroom, Bazaart, Snapseed, Canva, Remini, Adobe Express, VSCO, PicsArt, Polish, Lightroom, Instagram, and several camera apps.


First principles thinking: Breaking down to the smallest level - we found out that creating something on a blank canvas we would need a marker or something to hold and make, an eraser to undo mistakes, physically bend down on the table and focus our eyes on one small element inorder to edit that (painstaking). Thankfully its much easier digitally. Using the HCI principles, and mobile thumb control, the canvas was a real estate and we had to make good use of it, so in each tool we were creating these elements were crucial like undo/redo, erasor size, the ability to zoom in and out.

We realised that these are the very elements that helps a user be in control of their mistakes and to bring about the results they wished for. And it had to be easy to use. And the photos. The needed to be private and secure. To make the app flow like water, these were important:

Finding patterns: Psychological control & trust

Brush-first interaction

No tool selection, no mode switching. You upload, you brush. Intention is immediate.

Inline result preview

Results render in-canvas. No modals, no context loss. Continuity builds confidence.

Auto-size defaults

First-time users always picked the wrong brush size. A resolution-aware default cut failed erasures by ~40% before a single copy change.

The re-erase pattern

When AI fills weren't perfect, I designed a "undo/redo" loop instead of a restart.

Object selection & Spacial Control

First-time users always picked the wrong brush size. A resolution-aware default cut failed erasures by ~40% before a single copy change.

Loading and processing states

First-time users always picked the wrong brush size. A resolution-aware default cut failed erasures by ~40% before a single copy change.

Undo/redo logic and hierarchy

First-time users always picked the wrong brush size. A resolution-aware default cut failed erasures by ~40% before a single copy change.

The final result moment.

First-time users always picked the wrong brush size. A resolution-aware default cut failed erasures by ~40% before a single copy change.

A coherent studio

Scaling the tools & mobile app

Each new tool brought new UX challenges, but they all had to feel like one thing, not eight disconnected micro-products. The design system became the connective tissue. When a new component didn't fit, I fixed the system, not the component.

How studio was built

Magic Eraser: The original. Brush-based object removal. The founding UX model for the entire suite.

Background Eraser One-click removal with colour replacement. Built for e-commerce speed, designed for photographers and sellers.

AI Image Generater : Text-to-image creation. Open-ended generation required an entirely new UX model; no canvas to start from.

Background Blur : Depth-of-field effect with real-time intensity control. Designed for confident experimentation.

Bulk edit: 50 images simultaneously. The biggest UX lift is that the batch workflows without overwhelming the interface.

PRO Tier: Unlimited editing, 4K downloads, no watermark, priority support. Designed as capability, not gatekeeping.

Magic Eraser

The original. Brush-based object removal. The founding UX model for the entire suite.

Magic Background

One-click removal with colour replacement. Built for e-commerce speed, designed for photographers and sellers.

AI Image Generater

Text-to-image creation. Open-ended generation required an entirely new UX model; no canvas to start from.

Background Blur

Depth-of-field effect with real-time intensity control. Designed for confident experimentation.

Magic Background

The original. Brush-based object removal. The founding UX model for the entire suite.

Magic Background

The original. Brush-based object removal. The founding UX model for the entire suite.

What i had to invent

No playbook. So I wrote one.

Designing for generative AI in 2021–2024 meant there were no established patterns to reference. The AI Pattern Library I built for Magic Studio became the team's shared reference for every AI-powered interaction and the foundation for every tool that followed.

Impact

What happened after users were happy with Magic Studio (money)

  • Magic Studio grew to $2.3M in revenue with just 11 people. No marketing team. No paid ads. The product did the talking.

  • Every user came in organically. A no-signup wall meant people experienced the magic first and made a decision later. That single design call compressed the entire acquisition funnel.

  • 20M users. 150M images edited. Built on a seed round, staying lean, going global across 13+ languages without localisation ever being the bottleneck.

  • The competitors were well-funded giants: Lightroom, Photoroom, PicsArt, Adobe Express. Magic Studio outgrew them on word-of-mouth alone.

  • As the only designer, every interaction decision was also a business decision. Faster time-to-first-edit meant better activation. Cleaner error states meant less churn at the moments that mattered most.

  • PRO surfaced at the right moment meant revenue that didn't feel forced. Monetisation was a design problem, not just a pricing one.

  • Design wasn't a support function here. It was the growth strategy.

What i carried forward

How I would do this differently in 2026 with AI

  1. Research phase

In 2022, our user research took 3 weeks of interviews and synthesis. In 2026, I'd use Maze or Dovetail to run continuous passive research, auto-cluster session recordings into insight themes within hours. The same problem validated in 48 hours, not 3 weeks. Faster signal, same depth.

  1. Design Decisions

What I had to invent from scratch loading states for uncertain AI outputs, error states that don't destroy user trust. Today I'd reference Google's People + AI Guidebook and emerging component libraries from Material Design as a starting point, then diverge. I built the map. These are now the roads.

  1. AI Pattern Library

What I had to invent from scratch loading states for uncertain AI outputs, error states that don't destroy user trust. Today I'd reference Google's People + AI Guidebook and emerging component libraries from Material Design as a starting point, then diverge. I built the map. These are now the roads.

  1. What still AI couldn't have replaced

This is the most important line in the section. The judgment calls, the ethical guardrails, the decision to slow down and not ship a feature that felt wrong even when the data said to, that's yours. End the section there.

©vibhapolkam 2026

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