SDDL - Alternative to Branch.io for Deferred Deep Links

Hacker News

Hey HN! We just launched SDDL – a simple solution for creating deferred deep links for mobile apps. Think of it as a lightweight, Firebase-free alternative to Branch.io or AppsFlyer. What it does: • Generates short links like https://myapp.sddl.me/abc123 • Redirects users based on platform and install status • Passes data to the app after installation via Universal/App Links Why we built it: Branch.io and similar tools are powerful but often too heavy or expensive for small teams and indie devs. We wanted something simpler and transparent. Would love your feedback! We’re live and shipping fast – let us know what you’d want to see next. https://sddl.me

Visit product View on Hacker NewsMar 29, 2025

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

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best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user · 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: io · Missing: https docs, excited, just released

61%61% 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, users · Missing: plus, intuitive, reviews

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

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

51%51% 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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