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A platform for intentional human connections

Hacker News

A platform for intentional human connections

I created Compass — a free, open-source platform designed to help people find and form deep connections (platonic, romantic, or collaborative). I'm 28 and over the past years I got to connect with different people and hence get some clarity about who I am and what I'm looking for in life. More recently, I've been trying to find those people who align with my newly clarified values and life vision. I tried different approaches like dating apps, forums, and real-life communities, but I found it very slow and inefficient to find "my" people. Don't get me wrong, I got along with plenty of people there, but I'm sure there are highly aligned people among them that I just couldn't find because I lost too much time in the process of getting to know people I found interesting "enough". That got me thinking that there must be a more efficient way to find those rare people I'm looking for, a place where everyone puts a lot of info about themselves and their desires, and where it's fast to filter and sort them. I'm aware there are a lot of platforms that work great for specific types of connection already. LinkedIn is very efficient to find the people working in a specific company or studying in a specific school. Social media are (reasonably) good to chat and comment casually and with low commitments. Dating apps are good mostly for casual encounters, with more serendipity as their filters are very poor and you just see people one by one (for the people among us with a less agentic way of living, exploring profiles as they come—from some hidden matching algorithm usually). Yet, I just can't find a platform specifically designed to find the people I want to connect with more deeply and personally: a life partner, a close friend, a collab on a very specific project. I imagine a place where I can specify all my values and life goals in a long text and through checkboxes (kids, place to live, personality type, romantic style, thinking style, emotional style, conflict style, financial habits, culture, religion, politics, humor, triggers, dealbreakers, pet peeves, ethics system, work-life balance, housing,family projects, interests, intellectual topics, books, hobbies, etc.) and be presented with the most aligned (pre-filtered) people. I would then connect with them more deeply, through video calls or in-person events. So, the platform would be used to FIND people, not to foster the connection afterwards (as deep connections require in-person contacts or long video calls). That's my rationale for starting Compass. On the tech side, it's fully free and open source. The code, on GitHub thus, is in React / Typescript. Hosted in Supabase, Firebase and Google Cloud. It's owned / governed by the community; they make proposals and vote in a democratic way. The people who believe in the project give their time and money to keep it alive. There are only 250 people so far, but that's the vision I have for the platform. For data privacy reasons and to avoid data scraping, you need to sign up to view the profiles. But right now, to reduce all friction, you can sign up in 5 seconds (even with a fake email if you want, no email verification) without providing any personal info. Just enter an email address and password, and the rest is optional and skipable instantly. I actually already coded a pretty solid web app and just rolled out a WPA to get mobile notifications. Let me know your thoughts on that!

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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, agentic, google · Missing: mac, agents, macos
90%90% 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: created · Missing: supports, reddit linkedin, podcasting
89%89% 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
63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: personal, apps, video · Missing: mobile apps, ios, entrepreneurs
59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host, efficient · Missing: plus, intuitive, reviews
47%47% 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: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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