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TableSprint- Supabase alternative with vibe coding features

Hacker News

TableSprint- Supabase alternative with vibe coding features

We have built tablesprint for users to vibe code data structure and use our inbuilt APIs to get started. It also features airtable like or better capability in terms of UIs and Templates. While we have built lot of things on one Platform, you can vibe code various UIs on top of tables like forms,kanban,card,charts, calendar, gantt. We also feature micro app which works on mobile and Web both and where you can just combine screens, apply permissions and publish. Permission is another standout feature for us. Lot of integrations built in for notification, gmail, outlook, stripe and others.

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, stripe, coding · Missing: mac, agents, macos
98%98% 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
77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
42%42% 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: users · Missing: mobile apps, ios, personal
30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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