Fi

Find intersection area from at least 3 known distances and locations

Hacker News

Find intersection area from at least 3 known distances and locations

Hi HN, Have you ever wondered where is that mysterious place between 3 train stations from different walking distances? Introducing the doko.ninja! This handy tool is your go-to solution for determining the location of any mysterious spot. All you need is the distance from at least three locations, and our tool will pinpoint the intersecting area for you. It's easy and fun to use! We built Doko Ninja for our own internal use, but we thought it would be helpful for others too. So go ahead and give it a try. We'd love to hear about your use case and welcome any feedback or suggestions you have. Happy hunting!

Visit product View on Hacker NewsDec 30, 2022

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

60%60% predicted probability of success on AppSumo, 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 · Missing: supports, reddit linkedin, podcasting

52%52% 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

46%46% 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

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

27%27% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

9%9% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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