Hedge funds are hungry for new sources of alpha, but most efforts to apply artificial intelligence to stock picking have run into familiar pitfalls: data overload, unreliable models, and generative AI systems prone to hallucination. Fintech company Increase Alpha believes it has a different answer, and it just raised $3.5 million in funding to prove it.

The round was led by Bartt Kellermann, CEO of Battle of the Quants, a longtime convenor of hedge fund and quant finance discussions. The company’s founder, Sid Ghatak, is a former U.S. government AI policy advisor who has spent the past decade researching how predictive models can turn messy, public market data into usable trading signals.

A Crowded Field

Artificial intelligence is far from new to finance. From statistical arbitrage in the 1990s to today’s machine learning, investors have long sought ways to algorithmically predict stock movements. The latest wave has been fueled by large language models (LLMs), but their application to financial markets has been mixed.

A 2024 MIT study found that generative AI projects in banking and asset management delivered “little to no structural change.” The complexity of capital markets, combined with regulatory requirements for transparency, has made many off-the-shelf AI tools ill-suited for trading strategies.

A Purpose-Built Model

Increase Alpha positions its technology as an antidote to those shortcomings. Its platform, branded Predictive Artificial Intelligence (PAI), does not rely on generative AI. Instead, it is trained exclusively on public, compliant data such as company filings and disclosures, avoiding the regulatory gray areas that plague alternative datasets.

In trials, the engine has delivered 70% prediction accuracy across hundreds of equities, which is substantially higher than the 52 to 55% accuracy many hedge funds target. According to the company, this has translated into a 90% cumulative excess return over three years.

The model also promises ease of integration. Many funds spend months cleaning and normalizing third-party data before it can be fed into their systems. Increase Alpha says its signals are “ready-to-use,” which could lower barriers to adoption.

The company is not entering quietly. A recent research paper by the financial analytics firm Zanista titled “Increase Alpha: Performance and Risk of an AI-Driven Trading Framework” profiled Increase Alpha’s risk and performance framework, giving the company early validation. The firm also sponsored this year’s Eagle Alpha conference, where it presented to hedge fund managers, and Ghatak testified before Congress on AI’s role in improving care for U.S. veterans.

These moves suggest that Increase Alpha is as interested in building credibility as in pitching technology. “We are at an inflection point in fintech where predictive AI will become fundamental to investment strategies,” Ghatak said. “Our goal isn’t just to create another model, but to redefine how AI is applied in finance.”

Backers with Industry Clout

For Kellermann, the lead investor, the bet is not just on technology but on timing, particularly as hedge funds reevaluate how AI, blockchain, and digital assets fit into modern portfolio strategies. “After seeing how Increase Alpha merged AI, data, and hedge funds, I decided to invest,” he said. “This combination is so unique and effective that they have the potential to reimagine the entire hedge fund space.”

Industry veterans will note that similar promises have been made before. Quant startups often generate strong backtest results, only to struggle once their signals collide with real-world liquidity, transaction costs, and shifting market regimes. Increase Alpha’s trials suggest robustness, but broader adoption will hinge on how the system performs under stress.

From Classroom to Trading Floor

Ghatak’s path to fintech founder began in academia. At Villanova University, he led research into whether predictive engines could consistently forecast equity movements using only public data. The idea was simple: with the right model, compliance-friendly information could yield reliable signals. That work evolved into the foundation of Increase Alpha, validated through eight years of research and four years of live testing.

Now, the company is running pilots with several of the world’s largest hedge funds and is in licensing talks. Ghatak’s policy background may also help. He currently advises the National Artificial Intelligence Association and has worked with the White House on AI governance, giving him experience in bridging innovation with regulation.

Looking Ahead

The $3.5 million raise will fund go-to-market execution, including building relationships with Chief Investment Officers and portfolio managers, as well as onboarding new pilot customers. 

Increase Alpha says it already has multiple top-tier hedge funds trialing the system.

The stakes are high. If Increase Alpha’s claims hold true, its predictive engine could give funds a rare edge in markets where traditional sources of alpha have been steadily arbitraged away. But as with any fintech breakthrough, the burden of proof lies in live performance. For now, the company has bought itself time and capital to show that predictive AI can deliver where generative AI has fallen short.

This industry announcement article is for informational and educational purposes only and does not constitute financial or investment advice.