Peelaway – Turn photos into illustrations, prints, and miniature scenes

Hacker News

hey hn, i've been building peelaway, a tool for creating and editing images that starts with a curated gallery of visual styles. the idea is pretty simple: pick a style you like, then make something with a photo, a prompt, or both. you can turn a photo of your cat into a screen print, or try a paper-craft or miniature look. Peelaway started with image editing, and over time i moved the style gallery to the center of the product. i often heard users describing how hard it is to describe a style, so im interested in how much of the process can start with seeing something you like, instead of figuring out how to describe it. there’s also an api and mcp server if you want to use the editing tools from code or an agent. would love to hear what you try, where it falls short, and whether picking a style is a useful starting point for you. peelaway.io

Visit product View on Hacker NewsSep 18, 2026

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2points

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, mcp, user · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: users, way · Missing: mobile apps, ios, personal

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% 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.

Incorrect prediction on native model

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