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Supadash – an AI-generated dashboard to visualize your database data

Hacker News

Supadash – an AI-generated dashboard to visualize your database data

Hey everyone! I’m Mattia. I’m building Supadash ( https://www.supadash.co/ ), a tool that uses AI to generate a dashboard to visualize your database data. It’s like Retool only you don’t have to build charts but AI does it for you. While working on other projects, I found myself spending a lot of time making dashboards to visualize my apps’ data. I tried many tools like Retool but generally didn’t love the UX: I had to write SQL queries, retrieve the data in a specific format, and repeat the process for every single chart. It was kinda tedious and time-consuming, so I thought that using AI could make this process much more efficient. From there, I decided to build Supadash, with the focus on making it super easy and quick to get a dashboard for your app. You just need to connect your database and AI will generate charts to visualize your data in a few seconds. So far, it has helped me to save a lot of time building my own dashboards. Today I’m launching the “AI-generated dashboards” feature (so far the process was still sort of manual) and I’d love to hear your suggestions or feedback. You can try it and watch a demo here https://www.supadash.co/ and let me know what you think!

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, visual, single · Missing: mac, agents, macos
81%81% 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 · Missing: supports, reddit linkedin, podcasting
77%77% 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
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: apps, visualize · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · 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
19%19% 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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