Shortenr – A Powerful Link Tool

Hacker News

Hey HN, I’ve been building Shortenr — a modern, all-in-one link tool designed for creators, marketers, crypto users, and privacy-focused users. It includes: • End-to-End Encrypted File Sharing (client-side, using AES-256) • Smart Link Shortening (geo/device targeting, A/B tests, UTM builder) • Poll Links (gather user feedback from a short link) • One-Time & Expiring Links (perfect for stealthy content) • Link-in-Bio Pages with full analytics Everything’s built with privacy in mind — even file uploads are never stored in plaintext, and most features work without needing an account. I’m 15 and built this solo with TypeScript + Next.js + Prisma + PostgreSQL. Try it here: https://shortenr.me Would love feedback, feature ideas, or brutal critique!

Visit product View on Hacker NewsApr 30, 2025

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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.

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

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

9%9% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto, smart · Missing: web3, chat, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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