About Thomas Elnick
In a July 2024 interview, Tegus Co-Founder and Co-CEO Tom Elnick discussed the company's evolution and recent product developments. Elnick stated that Tegus, a subscription platform for institutional investors, aims to "take a lot of the grunt work out of the research process" by combining data and workflow tools. He noted that the company has completed three acquisitions and is now integrating those data sets into an "integrated investment platform" that ties together qualitative information, such as expert research and company filings, with quantitative financial data and key performance indicators.
Elnick also addressed the role of artificial intelligence at Tegus, explaining that the company uses AI to structure its large volume of unstructured proprietary data. He said this allows customers to "synthesize and digest it at a fraction of the time" and enables connections between qualitative data and other datasets like earnings calls and financial metrics. Elnick co-founded the company with his twin brother, Michael, describing the motivation as stemming from their own experiences in investment research and expert networks, where they felt "there has to be a better way."
Source: AI-verified profile updated from Thomas Elnick's recent appearances.
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Transcript (10 segments)
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Trinity0:00
T stands at the forefront of company intelligence platforms serving as the go-to solution for key decision makers worldwide. The co-founder and co-CEO Thomas Elnick is joining me today to talk more about how he navigates through some of the most challenging problems they are facing today only on Taking Stock.
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Thomas Elnick0:23
We sell a subscription platform for professional institutional investors. And so what we're trying to do is take a lot of the grunt work out of the research process, the manual gathering of data, the time-consuming, tedious, expensive parts of the research process, and ultimately making our customers more efficient and more effective. And really the way that we do that is through the right mix of data and workflow tools.
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Trinity0:48
Your identical brother Michael, you and him started this company, one of the fastest growing companies in Chicago. I mean, what was your motivation behind this, especially going into business with your brother?
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Thomas Elnick0:58
It's been an amazing journey. If you told me, Tom, you can start something with your twin brother, you know, it's kind of a pinch-me moment. But the way we got into the business is really a culmination of both of our backgrounds. So I used to work at a family office here in New York, a few years of really just doing deep fundamental research, kind of feeling like, gosh, there has to be a better way. And Mike was working at an expert network called AlphaSights, and from his vantage point also felt like, gosh, there has to be a better way as well. And so when you're 25, you kind of go on a journey and say, okay, let's go solve this problem.
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Trinity1:30
And you recently launched a new integrated investment platform. Tell me about this platform. Why is it so significant?
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Thomas Elnick1:37
We've done three acquisitions in our history. We are now integrating all of those data sets together, and it goes back to really building out this deep fundamental research platform from an end-to-end perspective. And so we are tying qualitative information and quantitative information. And when you think about what an investor's job is, it almost boils down to three legs of a stool: the expert research, you have the company perspectives, filings, earnings calls, investor presentations, and you have the financials, the KPIs, and the model. And now what we're doing is we're tying it together, we're connecting the dots for our users, and we're really applying the right workflow tools underneath it to make that whole journey a whole lot smoother.
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Trinity2:20
AI, it's at the forefront of many discussions around the world, especially here on Wall Street. Tell me about how you're integrating AI into your business model.
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Thomas Elnick2:28
Well, it all comes down to data and compute. And for us, we sit on lots of unique proprietary data. So a lot of our data is unstructured data. And so what we're doing with AI is we're taking all that unstructured data and we are structuring it in a way so that our customers can synthesize it and digest it at a fraction of the time that they have to go do it today. On top of that, what we're doing is we're now connecting the dots between our qualitative unstructured data that now gets structured via AI with other data sets, whether that's filings and earnings calls or financial data like the KPIs, net dollar revenue retention, CAC, rule of 40, etc. All of that now gets connected in a way that used to be incredibly difficult, and now we'll get it to you in a second. And it's all this data in one place, all the data in one spot.
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Trinity3:16
Well, thank you so much for joining me today. It was great to have you on Taking Stock.
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Thomas Elnick3:19
Thank you, Trinity. It was blessed.
