FlowSubs- Subscriptions Management

FlowSubs- Subscriptions Management

Indie Hackers

Stop losing money to forgotten subscriptions.

SaaS tools. AI apps. Streaming platforms. Domains. Hosting. Trials you forgot to cancel. FlowSubs helps you track, manage, and control every subscription in one clean dashboard — so you never get surprised by a renewal

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Actual performance

1followers
$140MRR/mo
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
TrustMRRFits verified-revenue profile · Strong signals: apps · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas, subscription · Missing: arr, mrr, revenue
38%38% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: apps, new · Missing: mac, agents, macos
38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host · Missing: plus, intuitive, reviews
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
27%27% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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