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Buzzcut – Make Your Apartment Buzzer Smart

Hacker News

Buzzcut – Make Your Apartment Buzzer Smart

Most apartment and condo buildings still rely on phone-based intercom systems. A visitor buzzes, your phone rings, and you press 9 to let them in. But if you miss the call or aren't home, you're out of luck. There's no easy way to grant remote access or see who’s coming and going. Buzzcut turns these buzzers into smart access systems. It lets you unlock your building door from anywhere, share temporary access links with guests or delivery drivers, set auto-unlock rules during certain times, and keep a log of buzz-ins. No hardware changes are needed—just link your buzzer to a virtual number managed by the app. It’s built with Flutter (iOS and Android support), a Python backend, Firebase, Twilio for virtual numbers, and RevenueCat for subscriptions. Group access control makes it easy to share access with roommates or family members. This started as a solution to a personal problem and is now being tested in a few buildings in Toronto. Still early, but looking for feedback, testers, and ideas. Would love to hear what you think.

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, ios · Missing: supports, reddit linkedin, podcasting
79%79% 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
63%63% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios, personal, way · Missing: mobile apps, entrepreneurs, apps
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
46%46% predicted probability of success on Product Hunt, 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
45%45% 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 · Strong signals: revenue, subscription · Missing: arr, mrr, profit
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
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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