Axtiva, app for your (digital) assets

Hacker News

https://play.google.com/store/apps/details?id=com.axtiva (please ignore the outdated screenshots, it looks much better inside) -- or just search for AXTIVA (blue "A" icon). Hi guys! Like many of you, over the time I've collected domain names for my "future startup" :) After I managed to sell some of them, the hobby turned into an addiction and the next thing you know, I have more than a hundred :) Another thing, I also like to hoard "lifetime deals," but, just like domain names, I'm terrible at managing my inventory. I created this app to scratch my itch. It's a work in progress. I'm very embarrassed to show this to be honest. Currently available on Android, but since it's Flutter expect iOS version soon. Stack: Flutter for frontend, Scala for backend, Dgraph for persistence, Quartz for scheduler.

Visit product View on Hacker NewsAug 7, 2020

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting

94%94% 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.

TrustMRRFits verified-revenue profile · Strong signals: ios, apps, google · Missing: mobile apps, personal, entrepreneurs

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

45%45% predicted probability of success on AppSumo, 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

34%34% 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 · Strong signals: google, apps · Missing: mac, agents, macos

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

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