Jack Kokko - Building AlphaSense - [Invest Like the Best, EP.404]
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How did AlphaSense evolve from fragmented data aggregation to an AI‑powered research platform?
I know firsthand how complex the tech stack is for asset management firms. And seemingly every new tool and data source makes the problem even worse, adding more complexity, more headcount, and more risk. Ridgeline offers a better way forward, one unified platform that automates away the complexity across portfolio accounting, reconciliation, reporting, trading, compliance, and more, all at scale. Ridgeline is revolutionizing investment management, helping ambitious firms scale faster. Faster, operate smarter, and stay ahead of the curve. See what Ridgeline can unlock for your firm. Schedule a demo at ridgeline.ai. Hello and welcome everyone. I'm Patrick O'Shaughnessy and this is InvestLike the Best.
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Patrick O'Shaughnessy is the CEO of Positive Sum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of Positive Sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Positive Sum may maintain positions in the securities discussed in this podcast. To learn more, visit psum.vc.
My guest today is Jack Coco. Jack is the CEO and founder of AlphaSense, where I and Positive Sum are Investors, an AI-powered search engine for market intelligence. He shares how AlphaSense began by aggregating fragmented financial data sources and evolved with the advent of large language models to completely change the research experience for investors and others. He speaks to the recent acquisition of Tegis earlier this year, reshaping the business and further supporting their expansion to serve all. Types of companies instead of exclusively investment firms. Jack has been navigating the AI revolution from its earliest days, and you can feel his excitement when he talks about the future. We discuss building an agile platform, the importance of managing cultural integration, balancing AI capabilities with user trust, and the frontier for this technology.
Please enjoy my conversation with Jack Coco. So, Jack, you are in a very unique position, having been one of the few entrepreneurs that was effectively building an AI product many years ago, before everyone was talking about AI, and using data and search and these tools probably for longer than just about anybody. So I think you're uniquely positioned to tell us what you've learned about applying the technology to build a great product. Today In late 2024. And maybe that's a perfect place to begin, which is just like a state of the union from you on what kinds of things AI enables for a product builder trying to serve a customer. What it unlocks. I'm also going to ask about what the limitations are today.
But since you've been doing it for so long, just give us that felt experience and then we'll talk about the future.
Well, maybe I'll start from the very beginning of what we are building with the prior generations of AI and machine learning. We wanted to build a semantic search engine that would understand financial and business content, read it line by line almost like a human analyst would, and understand all these billions of data points, millions of documents, and connect the dots between them, then map that to a user. Search query and deliver the right data points, the right insights to them. And this was really hard to do because all this content was siloed in thousands of silos in sort of paywalled data sources. It wasn't like the internet where Google and others had billions of web pages with links between them.
And those links would tell you about the authority of those pages and had billions of consumers clicking on pages that also What's good content, what's not so good content, and what's most relevant to a particular query.
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Chapters
8 chapters
1
How did AlphaSense evolve from fragmented data aggregation to an AI‑powered research platform?
0:00–7:25
2
What impact did large language models have on AlphaSense’s search and summarization capabilities?
7:25–14:27
3
How does AlphaSense balance powerful AI features with user trust and data provenance?
14:27–21:27
4
What lessons did Jack learn from the Tegus acquisition and how did it reshape the business?
21:27–27:33
5
How did AlphaSense break into the corporate market beyond investment firms?
27:33–33:10
6
What are the biggest challenges when selling AI research tools to investors versus corporations?
33:10–39:14
7
What does the future of AI‑driven market intelligence look like in the next five years?
39:14–44:47
8
What is the kindest thing anyone has ever done for Jack and how does it shape his entrepreneurial drive?
44:47–48:04
Speakers
1 identifiedMore from Invest Like the Best with Patrick O'Shaughnessy
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