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CalendarScan – Scan in events from any photo to your calendar

Hacker News

CalendarScan – Scan in events from any photo to your calendar

Today we are launching CalendarScan: an app that lets you take a picture of any calendar, schedule, or event and scan it directly to your phone using machine learning. CalendarScan also works with handwritten events, turning a planner or sticky note into a easy way of organizing your phone's calendar. CalendarScan will be free on IOS (to own, forever) and $0.99 on the Google Play store until March 1st. After March 1st it will be a one time fee of $4.99 with no subscription or ads. The CalendarScan web version and browser extension will be available February 1st.

Visit productView on Hacker NewsJan 18, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, google, using · Missing: agents, macos, agent
64%64% 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, google, way · Missing: mobile apps, personal, entrepreneurs
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
41%41% predicted probability of success on Hacker News, 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
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
29%29% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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