The People Behind The System
Why We Built GemAlgo
GemAlgo did not begin as a product. It began as a personal problem — and a refusal to accept that institutional-grade systematic investing was reserved only for institutions.
$250M+
Business Exits
30+
Years Investing
$50M+
Real Estate
Why GemAlgo Exists
After $250 Million In Exits, I Still Couldn’t Find Anywhere To Put The Money.
I’ve spent thirty years building and selling companies. Suncoast Research Labs sold for $200 million. I sold an Android TV brand to Google for $20 million. I scaled Set TV to $6 million a month in revenue. I’ve deployed over $50 million into real estate development and flips.
After those exits, I had a capital allocation problem that most financial advisors were completely unprepared to solve. I didn’t need help finding an investment. I needed something that would actually perform — not at 8% annually while inflation quietly erodes purchasing power, but at the level my businesses had generated.
"I looked at everything. Traditional investments felt stagnant. Private equity locked capital with uncertain outcomes. Hedge funds had $25 million minimums and still underperformed consistently. Nothing performed like my businesses had."
— Sean Beaman
And then I understood why. The investors who consistently outperform — Renaissance Technologies, Two Sigma, D.E. Shaw — are not analysts making predictions. They are engineers running systems. Mathematical, systematic, emotionless. They found the patterns in the data that humans cannot see, and they execute against those patterns with machine precision.
Jim Simons averaged returns over decades that no discretionary investor has come close to replicating. Not because he was smarter about markets. Because he treated markets as a mathematical problem — and built a system to solve it.
What he built with limited computing power decades ago, we can now dramatically enhance with modern artificial intelligence and machine learning. The insight remains the same. The infrastructure is orders of magnitude more powerful.
So I assembled a team. Quantitative researchers. AI engineers. Data scientists. And I gave them one rule above all others: preserve capital first. Build something I would trust with my own money. Because it was my own money.
Sean Beaman · CEO & Founder
Sean Beaman
CEO & Founder, GemAlgo
I grew up understanding that systems outlast individuals. The businesses that last — the ones that compound value over decades — are not built on the brilliance of a single person. They are built on processes that work regardless of who is operating them.
Over thirty years in finance, technology, and data, I applied that principle to every company I built. Suncoast Research Labs was a data and research business — we built systematic processes for collecting, cleaning, and monetizing data at scale. That sold for $200 million. The Android TV brand we sold to Google was built on operational systems, not individual expertise. Set TV scaled to $6 million a month in recurring revenue because the model was systematic, not dependent on heroic individual effort.
The common thread in everything I built was this: find the repeatable edge, remove the human variables, and scale the process.
$250M+
Total Exits
$200M
Suncoast Research Labs
$20M
Android TV → Google
$6M/mo
Set TV Revenue Peak
When I turned that same lens on investing, the conclusion was obvious and uncomfortable. Most investment strategies are not systematic at all. They are discretionary — driven by human judgment, emotional responses to market movements, and narratives that feel compelling until they don’t.
The quantitative funds that consistently outperform are the ones that have removed human judgment from the equation entirely. They have found the mathematical patterns in market behavior that repeat with enough frequency and magnitude to generate consistent returns — and they execute against those patterns with complete discipline.
I wanted that for my own capital. And I was not prepared to accept that it was only available to people who could write a $25 million check to a hedge fund.
So I built it.
What has changed is our ability to process those patterns at a scale and speed that was previously impossible outside of the world's largest quantitative hedge funds.
8-12%
Traditional
Portfolio Returns
50.71%
CAGR
GemAlgo’s Orion
Since Inception
Past performance is not indicative of future results.
GemAlgo started as my personal wealth engine. I had no intention of opening it to external capital. The system was built to manage post-exit capital — mine specifically — with the same rigor I applied to building the businesses that generated it.
After three years of verified, consistent performance with drawdowns that never exceeded what I was prepared to lose, I made a decision. The infrastructure was built. The track record was established. And I knew there were other people — founders, physicians, executives, investors — who had the same problem I had, and who deserved access to the same quality of solution.
That is what GemAlgo is. Not a fund. Not a black box. A systematic equities algorithm built for my own capital first — now available to a select group of investors who share the same standards.
Sean Beaman
CEO & Founder
$250M+
Business Exits
30+
Years Investing
$50M+
Real Estate
GemAlgo capital deployed alongside all investor accounts.
The Team
Built By Quantitative Researchers, AI Engineers, And Data Scientists.
After identifying the opportunity, the mandate was clear: merge institutional quantitative methodology with modern artificial intelligence. The team was assembled around that single objective.
Quantitative Research
The quantitative research team is responsible for signal architecture, factor construction, and strategy design. Their work draws directly on institutional quant methodology — the same mathematical frameworks that underpin the world’s most consistently successful algorithmic trading operations.
AI & Machine Learning Engineering
The AI engineering team builds and maintains the machine learning models that process 3 million data points per second across 222 distinct factors. These models identify institutional footprint patterns with a precision that was architecturally impossible without modern computational infrastructure.
Data Science & Risk
The data science and risk team is responsible for regime detection, position sizing models, drawdown controls, and continuous performance analysis. Their mandate: protect capital first, capture upside second. In that order. Always.
Our Commitment
What We Commit To Every Investor.
Full Transparency
Every trade visible in real time. Performance independently verifiable via third-party verification. No aggregated reporting. No selective disclosure.
Your Capital, Your Control
Funds remain in your own Interactive Brokers account. We have trade execution access only. Withdraw, pause, or disconnect at any time.
Continuous Research
Markets evolve. The system evolves with them. Signal performance, regime detection, and risk parameters are continuously monitored and refined.
Aligned Interests
GemAlgo capital operates in the same system as investor capital. Our incentives are structurally identical to yours. There is no version of this where our interests diverge.
Built For My Capital First. Now Available To A Select Few.
If the story resonates and the performance data meets your standards, the next step is a private methodology walkthrough.
— Sean Beaman, CEO & Founder, GemAlgo