I built a tool to create fast, beautiful QR code menus for restaurants

Hacker News

Hi HN, I built Morel after getting frustrated with how many restaurants replaced their paper menus with horribly slow, pinch-and-zoom PDFs after the pandemic. The user experience is just awful, especially if you have a bad connection inside a building. I wanted to build something better: a menu that felt mobile optimized, was incredibly fast, and just worked. Morel is a simple platform that lets restaurant owners build and host a lightweight and fast menu. The menu viewer itself is highly optimized for mobile phones and has minimal dependencies to ensure it loads instantly, even on a spotty 3G connection or weak restaurant Wi-Fi. The goal was to make it as close to "instant" as possible. Morel also lets you create and style QR codes that you can print. The tech stack is: * Frontend/Backend: Next.js / React * Database: PostgreSQL with Prisma * Payments: Stripe * Auth: Clerk I've just launched and would love to get your feedback on the product, the tech, or any other aspect. I'll be here to answer any questions. The site is at: https://www.getmorel.com Thanks,

Visit product View on Hacker NewsAug 26, 2025

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

88%88% 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.

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

68%68% predicted probability of success on Product Hunt, 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

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: platform, host · Missing: plus, intuitive, reviews

53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

17%17% 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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