Oasis, the community tech collective building an advocacy flywheel

Hacker News

Hey everyone, I wanted to share the project I recently launched called Oasis, which is a community-driven tech collective with the focus of driving social advocacy by creating a self-sustaining flywheel of open-core projects that feeds into our various social advocacy initiatives. The governance is set up much like Open AI, where Oasis is the non-profit that handles the social advocacy and acts as an umbrella for the various OSS projects, and we have a collective structure of contribution with shared ownership so everyone who is working on a project, while it being OSS, gets to share in the financial success. We're 100% community driven, and anyone can join the Slack workspace now and contribute to any of the repos, but to actually be an "owner" we do require a $200/yr membership fee to help offset operational costs of adding users. All the projects we work on are thoroughly researched for profit potential and technology stack, and currently the angle we've been focusing on a lot of finding closed-source software and essentially ripping their features out into open-core versions. Tangentially, if you have a software you'd love to see a open-core version of then add a comment in here for sure. We're mainly been playing with simple CRUD apps but should the collective grow there's potential for other types of projects.

Visit product View on Hacker NewsJan 30, 2024

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, 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

38%38% 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: users · Missing: plus, platform, intuitive

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

20%20% 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

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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