Ringer – Get and provide expert help on Open Source Software

Hacker News

Hello HN, Over the past few months we've been building Ringer, an Experts Marketplace focussed on Open Source Software. We want to help make Open Source more sustainable and believe that we can be a part of making that happen. We're approaching this from the perspective of the individual developer - if you contribute to OSS then you can register instantly with your GitHub account and list yourself to provide paid support, knowledge and help for the repositories that you contribute to. We only allow those who we can prove contribute to repositories to list themselves as experts, and show details of contribution history for the experts in the system so that customers can see exactly how the experts can help. We process payments to over 100 different countries via Stripe, and handle all of the paperwork to make the process as frictionless as possible, including 1099s for US based experts. We're building out tools to improve the developer experience at the moment, and have started to work with customers to design a process that allows them to access expertise quickly whilst working within the constraints of an enterprise environment. For the past 3 or so weeks we have been in an Alpha stage, so this is our Beta launch - we are really open to fresh ideas and opinions. From day 1 I have said to every developer that I have spoken to that whether you love the idea or hate it, all I want to know is why and what we can do better - so HN, please tell me what you think and want it to be!

Visit product View on Hacker NewsSep 8, 2022

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

85%85% 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, including · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

77%77% 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: month · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

26%26% 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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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