ZF
ZF Grants – Grants and Community Funding in $ZEC
Hacker NewsZF Grants – Grants and Community Funding in $ZEC
The Zcash Foundation’s new platform for grants and community funding, ZF Grants, is open for proposals! The Foundation plans to dispense the Zcash equivalent of $500,000 through ZF Grants in 2019. As one of the contributors to this project, I'm super interested in hearing what the community here thinks. You can learn more about ZF Grants at https://grants.zfnd.org/ and https://www.zfnd.org/blog/zf-grants-is-ready/ Happy to field any questions about the platform :)
Share cardActual performance
5points
1comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, open · Missing: mac, agents, macos44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting40%40% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue17%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, crypto14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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