Nomad Atlas: Curated travel advice from your friends

Hacker News

Over the last decade, I travelled to over 65 countries. Everytime I landed in a new city I would look up which of my friends had been there and ask them for some recommendations on where to eat, where to stay etc. After doing this many times I realized others could benefit from this too so I created Nomad Atlas. On Nomad Atlas you'll find curated travel guides from your friends, celebrity chefs and taste makers. During Covid I wanted to learn Golang so I wrote the backend in Go and this is the result

Visit product View on Hacker NewsAug 3, 2022

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

61%61% 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.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

47%47% 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 · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% 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

25%25% 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

13%13% 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

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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