I

I built a simple tool because I was tired of clunky background removers

Hacker News

I built a simple tool because I was tired of clunky background removers

I do a lot of design work, and one thing that always annoyed me was how unreliable background remover tools can be. Some are too slow. Others mess up the edges. And most of the free ones slap on watermarks or force you to sign up just to download. So I decided to build my own. I kept it clean, fast, and focused only on what matters: removing backgrounds accurately, especially around the edges. No login, no watermark, just drop an image and go. It’s not fancy — just something I actually wanted for myself. If you want to try it out, here’s the link: https://edge-aware-ai-cut.lovable.app/ Would love to know what you think or how it could be better.

Share card

Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released
35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: lovable · Missing: mac, agents, macos
26%26% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

A
A Simple Background Generator I Made39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A Simple Background Generator I Made

Hacker News3
Ch
Chard – simple async/await background tasks for Django37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Chard – simple async/await background tasks for Django

Hacker News61
Background Generator
Background Generator37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

a simple background generator

Indie Hackerscommitment-side-project
We
We built a tool for RISC-V alphanumeric shellcoding36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

We built a tool for RISC-V alphanumeric shellcoding

Hacker News1
Re
ReflectOps – I built tool for retrospectives36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ReflectOps – I built tool for retrospectives

Hacker News1
I
I built a refund tool for late deliveries – here's what happened47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I built a refund tool for late deliveries – here's what happened

Hacker News2
A
A simple cryptanalysis tool for the Vigenere cipher45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A simple cryptanalysis tool for the Vigenere cipher

Hacker News4
Ba
Baker – a simple tool for baking vms and containers62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Baker – a simple tool for baking vms and containers

Hacker News4
Wi
Windo, a Simple Timezone Tool45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Windo, a Simple Timezone Tool

Hacker News3
Ra
Rakoshare, a simple syncing tool39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Rakoshare, a simple syncing tool

Hacker News1