Distributed location data analytics for mobile apps

Hacker News

The DLDB is a distributed location (and private data) analytics for mobile applications. It enables the understanding of end-user movement patterns and provides the content of different locations. DLDB is about privacy and scaling. More about DLDB can be read here https://dldb.io/ and here https://github.com/dldbdev/articles/blob/main/about.md The beta version for the SDK is available at https://github.com/dldbdev And the beta version of our dashboard is here: https://dashboard.dldb.io/ All questions, comments and critiques are more than welcome!

Visit product View on Hacker NewsJul 5, 2022

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user · Missing: mac, agents, macos

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.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

17%17% 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

8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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