Baseboard – Query and visualize your data in plain English

Hacker News

I made baseboard. A tool to query and visualize your data in plain english. For example, if you have sales database, you can connect it and "say visualize revenue split by state in a pie chart" and it will generate that for you. It just takes 2 minutes to sign up (email only) and a sample data source is added when you register. Looking forward to hearing your feedback on this!

Visit product View on Hacker NewsJun 6, 2023

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Actual performance

1points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, visual, plain · Missing: mac, agents, macos

78%78% 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.

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

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

35%35% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

35%35% 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

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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