Alprina – Intent matching for co-founders and investors

Hacker News

We noticed that professional networking is mostly profile-based: you create a static resume and hope the right people somehow discover you. But what actually drives meaningful connections is complementary intent: a founder looking for a technical co-founder, an engineer wanting to join a specific type of early-stage company, an investor actively looking for a certain thesis. We built Alprina to match people on what they want right now, not just who they are on paper. On Alprina, you create "intents" in natural language (what you're looking for), join networks (communities where matching happens), and our AI matches you with people whose intents complement yours. You can attach context like pitch decks or profiles so that when you match, the other side immediately understands why you're reaching out. Would love feedback from the HN community - especially on the balance between match precision and serendipity. Too strict and you miss interesting connections; too loose and it's just noise.

Visit product View on Hacker NewsJan 26, 2026

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

69%69% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

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

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

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

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% 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 · Strong signals: active · Missing: arr, mrr, revenue

17%17% 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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