Bookmarks in one smart place with SaveTo

Hacker News

How often do we save links or texts that we then never retrieve because we forget where they are or simply cannot remember the name of the website? This happens to me often, so I decided to create SaveTo, a simple cross-platform app that allows you to save links that can then be retrieved via chat, without having to remember the exact name of a website or link library. I've just opened the waitlist, and any feedback is welcome!

Visit product View on Hacker NewsJul 23, 2025

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

66%66% 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.

Hacker NewsStrong engagement from HN community · Strong signals: ide · 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.

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

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

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

51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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