Deploy OpenClaw in 60 seconds – one-click setup, no DevOps needed

Hacker News

Hey HN — I built openclawsetup.tech after seeing dozens of comments about people giving up on OpenClaw's setup process. The traditional setup (VM, SSH, Node.js, API keys, messaging channels) takes 60+ minutes. This reduces it to 3 clicks: sign in, choose a model, deploy. Managed hosting handles the infrastructure. Free tier available. Would love feedback from this community.

Visit product View on Hacker NewsFeb 26, 2026

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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

67%67% 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

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

33%33% 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

29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

18%18% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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