Fide – Crunchbase for Web3 Projects and People

Hacker News

Hi HN! I’m Chris, Co-founder of Fide. When contracting for Celsius in 2019, a recently bankrupt crypto-lending platform, I quickly observed how important it was for every Web3 company to establish credibility and trust in a high-risk industry where fraud and scams are becoming increasingly common. As I continued to invest and build in the space, it became clear that existing tools are still not enough to effectively evaluate credibility. Common issues that keep coming up include: 1. Repeat scammers are rarely held accountable 2. Anonymous contributors can’t easily establish credibility 3. Project and contributor success metrics are mostly based on historic financial performance We built Fide to help users verify web3 credibility and only invest in projects and teams they can trust. We’re still adding features and projects but would welcome any feedback as we continue building!

Visit product View on Hacker NewsSep 14, 2022

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

55%55% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, lua, existing · 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.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

29%29% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: web3, crypto · Missing: chat, cryptocurrency, make money

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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