Bytesweep

TrustMRR

Bytesweep develops and sells desktop software for macOS and Linux that shows people what is using their disk space and helps them reclaim it safely. The app scans a drive locally and visualises it in

Bytesweep develops and sells desktop software for macOS and Linux that shows people what is using their disk space and helps them reclaim it safely. The app scans a drive locally and visualises it in eight views, identifies reclaimable data — Docker images, Xcode caches, local AI models, duplicates, old installers — and warns before removing anything that cannot be recovered, such as SSH keys or unpushed git history. Every sweep is undoable for seven days. We sell a single one-time licence for $

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Actual performance

Did not reach leaderboard

Launch Intel predictions

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

82%82% 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.

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

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

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

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

20%20% 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

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

Correct prediction on native model

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