Data Apps for Everyone

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I'm Tevon, founder of Bruinen. I started Bruinen because at a previous company I found myself constantly building out internal apps that were essentially a wrapper around a database table, they had some permissions, some actions that could be taken, a couple charts, and a database. With Bruinen, we've made creating data apps like this simple, and useable by non-engineers as well as engineers. We model everything as an object, so that each "Object Blueprint" contains all the information needed to properly permission, display, and provide actions on that object. We just launched our self-service product and would love to get your thoughts!

Visit product View on Hacker NewsJan 23, 2024

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Launch Intel predictions

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

94%94% 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: started · Missing: supports, reddit linkedin, podcasting

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

64%64% 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: apps · Missing: mobile apps, ios, personal

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

35%35% 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

20%20% 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.

Incorrect prediction on native model

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