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KelAI Raises $5M to Build an Autonomous Research Engine for Hedge Funds – AlleyWatch

by theadvisertimes.com
22 hours ago
in Startups
Reading Time: 4 mins read
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KelAI Raises M to Build an Autonomous Research Engine for Hedge Funds – AlleyWatch
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Institutional investing has long operated on a simple but costly constraint: research capacity scales with headcount, and headcount scales slowly. The world’s largest systematic hedge funds – managing assets that collectively exceed $5T globally – built their edges by deploying armies of quantitative researchers, yet even elite teams at firms like Millennium Management and WorldQuant face limits on how many signals they can test, how many datasets they can explore, and how quickly losing hypotheses get retired. The result is a fragmented research process where valuable insights scatter across siloed systems, live signals decay undetected, and portfolio managers receive feedback loops measured in weeks, not hours. KelAI addresses this directly by offering an autonomous AI research engine that runs the full investment research loop – from idea generation and backtesting through signal validation and live monitoring – inside a single agentic platform that compounds knowledge with every iteration. The company’s signals have been running with an institutional investor since October 2025, moving the platform beyond theory into production alpha.

AlleyWatch sat down with KelAI Founder & CEO Jeremie Cohen to learn more about the business, its future plans, recent funding round, and much, much more…

Who were your investors and how much did you raise?

We raised a $5M seed round from Frst, Y Combinator, Robinhood Ventures, and a group of angel investors from the AI and finance industries.

Tell us about the product or service that KelAI offers.

KelAI is an AI research engine for hedge funds and institutional investors. We help investment teams expand their research capabilities.

What inspired the start of KelAI?

After spending years inside leading hedge funds, I saw how much investment research remained limited by human time. Advances in AI created an opportunity to rethink that.

How is KelAI different?

KelAI combines advanced AI with deep investment expertise. It was built specifically for hedge funds by people who understand how institutional research works.

What market does KelAI target and how big is it?

We serve hedge funds and institutional asset managers. It is one of the world’s largest industries, managing well over $100 trillion globally.

What’s your business model?

KelAI operates an enterprise software model.

How are you preparing for a potential economic slowdown?

We are staying  focused on building something the industry needs in every market environment.

What was the funding process like?

It was intense and highly focused. We chose investors who share our long-term view of AI’s role in institutional investing.

What were the biggest challenges you faced while raising capital?

We were fortunate to have a smooth process. Our focus was choosing partners who understood both AI and institutional investing and shared our long-term vision.

What factors about your business led your investors to write the check?

Our domain experience, clarity of vision, and speed of execution.

What milestones do you plan to achieve in the next six months?

We will continue improving the product, grow our New York team selectively, and execute with focus.

What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?

Protect your runway, stay close to customers, and focus on work that creates measurable value.

Where do you see the company going over the near term?

We are focused on building KelAI into a category-defining company at the intersection of AI and institutional investing.

What’s your favorite summer destination in and around the city?

I enjoy escaping to the Hudson Valley or nearby Connecticut. Both are close to the city and offer a refreshing change of pace.

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