Overview
Thomas Li is co-founder and CEO of Daloopa[1], an AI data infrastructure platform for financial institutions[3]. Li studied finance and economics at New York University[8]. Prior to founding Daloopa in July 2019[4], Li worked as a TMT analyst at Point72 Asset Management from 2015 to 2017[7], followed by roles as an analyst and partner at KCL Capital from 2017 to 2018[6] and in TMT credit and equity at Angelo, Gordon & Co. from 2018 to 2019[5].
Profile introduction
Daloopa builds AI data infrastructure for financial institutions
Career history
- Co-Founder / CEOJul 2019 to PresentDaloopa
- TMT Credit & Equity2018 to 2019Angelo, Gordon & Co.
- Analyst / Partner2017 to 2018KCL Capital, L.P.
- TMT Analyst2015 to 2017Point72 Asset Management
Education
Finance, EconomicsNew York University
Insights & ideas
The through-line
Across appearances, Li returns to one wager: that trustworthy, structured data is the real bottleneck in financial analysis, more consequential than model intelligence itself, and that Daloopa exists to solve for that bottleneck so AI can be applied on top of it. Early on this was framed as a data business competing against a legacy oligopoly [7][8]; more recently the framing shifted toward explicit AI workflows built on top of that data foundation, with Daloopa's verified historicals positioned as the context layer for large language models like Claude [4][5][10]. The constant is skepticism that better algorithms alone win in this space, paired with confidence that verified, well-structured data is the harder and more durable asset [7][8][10].
On the data oligopoly and why Daloopa exists
He founded Daloopa in 2019 out of a buy-side analyst's frustration, with an explicit goal of capturing market share from the entrenched data providers Bloomberg, FactSet and Capital IQ [7][8]. Discussion of this origin covers how he views these legacy providers and what set his approach apart from them [7]. Central to that positioning is making Daloopa a must-have rather than a nice-to-have for analysts and portfolio managers, a distinction he treats as the real test of product-market fit in a market dominated by incumbents [7].
On why the model isn't the differentiator
Li argues that in applying AI to investing, the contextual data fed into a model matters more than the quality of the algorithm itself, and he works through how firms of different sizes are adopting large language models around note synthesis, risk modeling and center book evaluations [10]. He addresses AI's particular strength in generating language versus other analytical tasks, and discusses where large language models currently fall short in financial analysis [10]. This view carries directly into how he frames Daloopa's own product: verified historicals functioning as trusted context that a model such as Claude can use as a thought partner, with a retrieve-then-analyze workflow described as the practical shape of an AI stack for fundamental investors [4]. He also discusses the company's work on eliminating hallucination while scaling AI-driven workflows for analysts [5], and describes a sharp, more-than-100x increase in data consumption on the platform, attributing it to something other than the underlying model itself [8].
On selling complex or deep tech
Li discusses the challenge of explaining complicated technology in simple terms to both investors and customers, distinguishing how that pitch should differ between the two audiences [2]. He also addresses who the primary targets are when raising money for a deep tech company like Daloopa [2].
On building a durable data business
He emphasizes the importance of building a company that naturally generates significant cash, treating that discipline as core to the long-term viability of a data business rather than a secondary concern [7].
On open-sourcing the investor library
In his most recent appearance covered here, Li addresses a move toward opening up an "investor library" of data, marking a shift in how Daloopa's resources are made available to the market [6].
On the semiconductor industry
Drawing on his background as a TMT analyst, Li takes part in a discussion of Intel's decline from its position as the semiconductor industry's gold standard, covering its lag behind the AI curve, declining margins, internal dysfunction, and whether new leadership can reverse the company's trajectory [9].
Takeaways
- Founded Daloopa in 2019 with the explicit goal of taking market share from Bloomberg, FactSet and Capital IQ [8].
- Treats "must-have versus nice-to-have" as the real bar for product-market fit against legacy data incumbents [7].
- Argues the differentiator in financial AI is contextual, verified data rather than the underlying model or algorithm [10][8].
- Positions Daloopa's verified historicals as the trusted context layer feeding large language models like Claude in a retrieve-then-analyze workflow [4].
- Frames eliminating hallucination as central to scaling AI workflows for analysts [5].
- Considers cash generation a foundational discipline for building a lasting data company [7].
- Adjusts the pitch for selling deep tech depending on whether the audience is a customer or a fundraising investor [2].
Media & appearances
- Invest with AIApple PodcastsDaloopa CEO Thomas Li: The Magic Isn’t in the ModelFormer Point72 TMT analyst Thomas Li left the buyside to build Daloopa in 2019 with the goal of capturing market share from the data oligopoly of Bloomberg, FactSet and Cap IQ. Last year data consumption on the platform grew over 100x, and it wasn't the
- The Hedgineer PodcastApple PodcastsSeason 2 Finale: Open-Sourcing the Investor Library with Daloopa CEO Thomas Li | S2E10Season 2 Finale: Open-Sourcing the Investor Library with Daloopa CEO Thomas Li The Season 2 finale of The Hedgineer Podcast features the return of Thomas Li, Co-founder and CEO of Daloopa, for his third appearance on the show. This episode marks a signi
- InDaloopApple PodcastsBuilding the Analyst’s AI Stack: Inside Anthropic x DaloopaThomas Li (CEO, Daloopa) and Nick Lin (Anthropic) go deep on a practical AI stack for fundamental investors: Daloopa’s verified historicals as the trusted context, Anthropic’s Claude as the thought partner. They unpack the “retrieve → analyze
- The Hedgineer PodcastApple PodcastsAI in Finance: Eliminating Hallucination & Scaling Workflows w/ Daloopa CEO Thomas Li | S2E1Welcome back to the Hedgineer Podcast! We're kicking off Season 2 with one of our favorite guests, Thomas Li, Co-founder and CEO of Daloopa (https://hubs.ly/Q03C7TSR0). In this episode, we delve into the significant advancements Daloopa has made, includ
- InDaloopApple PodcastsHow Intel Lost the Chip War — And Whether It Can Be SavedOnce the gold standard in semiconductors, Intel now finds itself years behind the AI curve, with declining margins, internal dysfunction, and an identity crisis. Can a new CEO with a quiet but proven track record bring it back? In this episode of InDalo
- Yet Another Value PodcastApple PodcastsAI in Investing with Daloopa's founder Thomas LiIn this episode of Yet Another Value Podcast, host Andrew Walker shares a webinar conversation with Thomas Li, CEO and co-founder of Daloopa, diving into how AI is transforming the workflows of fundamental investors. They explore real-world applications across hedge funds and investment banks, highlighting both the promise and current limitations of large language models in financial analysis. From note synthesis to risk modeling and center book evaluations, Thomas outlines the practical realities of AI implementation, discusses adoption across firm sizes, and explains how contextual data—not just algorithm quality—is becoming the differentiator. Whether you're a solo analyst or part of a multi-manager platform, this episode offers a grounded perspective on where AI in finance is heading.__________________________________________________________[00:00:00] Andrew introduces the episode as a repost of a webinar with Daloopa on AI and investing.[00:01:58] Thomas Li outlines AI’s strength in generating language vs.
- Compounders PodcastApple PodcastsThe Underappreciated Power of Data Companies with Thomas Li, Co-Founder and CEO of DaloopaMy guest on the show today is Thomas Li, the co-founder and CEO of financial data company Daloopa. Daloopa is a private company that was founded by a group of former buy-side investment analysts who saw the opportunity to use technology to upgrade the research process at just about any type of investment firm; but with a specific focus on saving analysts and portfolio managers time. Just a few years into its journey, the company already has over 200 employees and has multiple offices around the world. In this wide-ranging interview, Thomas and I discussed: Where the original idea for Daloopa came from; How he views the legacy data providers such as CapitalIQ and Bloomberg; What Daloopa is doing to make the product a must-have versus a nice-to-have; What AI means within the context of Daloopa; and The importance of building a company that naturally generates a lot of cash As a disclaimer, Daloopa is a sponsor of the Compounders podcast. Cove Street nor Ben Claremon are shareholders of Daloopa. Without any further ado, here is my conversation with Daloopa CEO Thomas Li. For more information about Daloopa, please visit: https://daloopa.com/ This episode of Compounders: The Anatomy of a Multibagger is sponsored by Daloopa. Daloopa was founded by a former hedge fund analyst to bring simplicity to the investment process.
- Bank On ItApple PodcastsEpisode 501 Thomas Li from DaloopaThis episode was produced remotely using the standardized audio & video production system. If you’re looking to jumpstart your podcast miniseries or upgrade your podcast or video production please visit You can subscribe to this podcast and...
- Bank On ItApple PodcastsEpisode 500 Rohin Tagra from Azimuth GRCThis episode was produced remotely using the standardized audio & video production system. If you’re looking to jumpstart your podcast miniseries or upgrade your podcast or video production please visit You can subscribe to this podcast and...
- The AFT podcastApple PodcastsSelling complex tech to investors and customers - how Daloopa made it in FinTech. By Thomas LiAt the Forefront of Transactions | Payments | Fintech | Pay-tech | Banking: Thomas Li, Co-Founder and CEO at Daloopa talks about explaining complicated tech in simple terms and selling it to investors and buyers. We also discussed deep tech in greater detail and who are the primary targets for fundraising in these cases. We als
- The Hedgineer PodcastApple PodcastsEp. 6: Using AI to Build One of the Best Datasets for Investing
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