rule30: Would we back your startup + why
Share your LinkedIn. Receive a decision + reasoning in 24h.
86 followers
Share your LinkedIn. Receive a decision + reasoning in 24h.
86 followers
Every financial market eventually yields to systematic investment strategies. VC is next + rule30 is leading that shift with a fully algorithmic, index style approach to identify outlier founders at scale We’ve built an AI decision engine that reasons probabilistically about early stage investing, moving beyond hype cycles + pattern matching It identifies outliers by ranking founders into percentile bands (top 10%, 3%, 0.1%) - a new category in venture: algorithmically curated outlier founders
Hey everyone 👋 The rule30 team here, excited to share what we’ve been building!
Every financial market eventually yields to systematic investment strategies. Venture Capital is next - and rule30 is leading that shift, using a fully algorithmic, index style approach to identify outlier founders at scale.
We’ve built an AI decision engine that reasons probabilistically about early stage investing, moving beyond hype cycles, pattern matching, and gut feel. It identifies outliers by ranking founders into percentile bands (top 10%, 3%, and 0.1%) - creating a new category in venture: algorithmically curated outlier founders.
Our name comes from Wolfram’s “rule 30” - a simple algorithm that generates infinite complexity. From that inspiration, our system uncovers hidden structure in the chaos of startups, showing what’s inevitable before it’s obvious.
How it works:
Share your LinkedIn, and within 24 hours you’ll receive a report that includes:
A clear yes/no decision
Structured reasoning (not a superficial “AI score”)
Your percentile band - a signal of outlier potential
This isn’t a demo or a scorecard.
It’s a real investment decision, fully algorithmic, with no humans in the loop, and the first public glimpse into how our fund actually invests.
Why it matters:
For founders → a credible market signal
For angels → early visibility on breakout potential
For LPs → proof that venture will yield to systematic strategies
Try it! See where you rank → https://founder.rule30.vc/signup
Founderfit by Koble
Guy & Damian here, the team behind rule30, an AI research lab for venture with its own fund.
Venture has been guessing for decades - stories, pattern matching, gut feel. But every industry eventually yields to AI, and every financial market to systematic strategies. Venture has resisted that inevitability… until now.
We believe research, data, and compute will power the next generation of venture funds. At the centre of that vision is rule30’s probabilistic, fully algorithmic investment decision engine.
And for the first time, you can see it at work.
Share your LinkedIn. In 24 hours, you’ll know if we’d back you, which percentile band you fall into, and why.
This isn’t a score, and it’s not a gimmick.
It’s a real investment decision - fast, reasoned, and with no humans in the loop.
The name comes from Wolfram’s Rule 30 - a simple algorithm that generates infinite complexity. From that inspiration, we’ve built a system that uncovers hidden structure in startup chaos, showing what’s inevitable before it’s obvious.
Why launch here? Because the best founders are on Product Hunt, and we want you to see rule30 first.
Try it. Share it. And if you get a yes… watch what happens next ;)
• Guy & Damian @ rule30
Insight Pipeline
Super idea. Website looks slick. Where do you source your data from?
@davidbatey Thank you!
The system pulls in large volumes of unstructured company and founder data from multiple sources, feeding data to a proprietary predictive deep learning model that calculates the probability of success for startups. We also built 14 other classification and generative models, to create a rich data set that feeds the Winner Predictor model features.
So in addition to LinkedIn, we pull raw data from multiple sources like: Crunchbase, Pitchbook, UK Companies House, PeopleDataLabs, WebArchive, Meta, Moz, LinkedIn, Twitter and over 4.4 million company websites using custom made web scrapers.
Votebox
Cool project !
This looks really cool, I’ve been waiting for someone to take this approach to VC for years
@james_kilpatrick1 thanks for your support!
Super cool, congrats Guy, Damian and team on all your hard work! Excited to see you go from strength to strength
thanks @ry_paddy appreciate the support!
This is a bold idea—using an algorithm to find standout founders instead of just going by gut feeling. Ranking founders into tiers (top 10%, 3%, etc.) gives a clear signal instead of vague feedback.
A practical question: Are you mainly looking to help early founders see where they stand, or are you also aiming to help angel investors find promising startups faster?
(I ask because I work with founders and early investors on LinkedIn, where these conversations about startup potential and investor matchmaking happen every day.
@penny_w
@olajiggy321 thanks and great question!
The short answer is: both groups benefit, but in different ways.
For founders, the goal is to offer a clear, structured signal, not a vague or subjective impression. It gives them transparency into how a systematic investor sees their trajectory and potential.
For angels and early investors, the value is widening surface area. Our system helps them identify outlier potential earlier and with more consistency.
So the same engine supports both sides, but the purpose differs:
- Founders get clarity and transparency
- Investors get earlier visibility into outlier trajectories
Would love to hear how this fits with the conversations you’re having!
@penny_w
You’re creating a new category—algorithmic investing. The biggest hurdle won't be the tech, but getting founders and investors to understand and trust it.
The conversations that will drive adoption are already happening on LinkedIn, where founders seek feedback and investors hunt for signals. I help technical platforms enter those conversations with clarity.
If it's useful, I can show you how to message rule30's value to both audiences in the channels where they're already listening.