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Dan Entrup

Co-Founder, Aggknowledge

Search every verified Dan Entrup interview, podcast appearance, and on-the-record quote — each transcript cross-checked by AI and human review to confirm speaker identity. Dan Entrup, co-founder of Agknowledge, appeared on the Hedgeineer podcast in March 2026 to discuss data procurement and strategy in asset management and AI. He argued that the traditional model of purchasing financial data—characterized by opaque pricing and rigid, six-figure bulk contracts—is misaligned with the needs of modern AI development, advocating instead for data liquidity and consumption-based purchasing. He noted that consumption-based pricing does not necessarily mean lower prices or reduced contract values, citing mechanisms such as platform aggregation and committed minimum spends that can smooth cash flow, similar to cloud computing models. Entrup also commented on the state of the ML data marketplace, describing it as "in a pretty sorry state of affairs." He said that selling data to large foundational model labs often requires significant upfront capital to create sample datasets and pursue product-led growth strategies, with uncertain prospects of being contacted by the labs' financial or partnerships teams. He contrasted the buyer profile for AI and ML companies—focused on engineers and researchers—with that of traditional financial services clients.

Recent appearances

  • The Research Industry's Self-Inflicted Wound | Signal & Noise Ep 36

    June 03, 2026 · 📺 Signal and Noise

    In this episode, Brian and Andrew sit down with Dan Entrup, co-founder of AggKnowledge, to talk about one of the most overlooked drivers of the data quality crisis: the respondent experience nobody is actually fixing. Dan tracked every research outreach he received over 15 months and turned it into a SampleCon presentation. The numbers were brutal. 137 times asked his age. 57 dental requests sent to someone who has never been a dentist. An inbox so flooded with irrelevant surveys that even a motivated expert panelist nearly quit. His point is sharp: bad targeting is not just inefficient, it i…

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  • Data Liquidity and the Agentic Marketplace: Moving Beyond Bulk SaaS Contracts | S2E8

    March 17, 2026 · 📺 The Hedgineer Podcast

    The traditional model of purchasing financial data is structurally misaligned with the requirements of modern AI development. While hedge funds have historically navigated opaque pricing and rigid, six-figure bulk contracts, the rise of Frontier Labs and agentic workflows demands a shift toward data liquidity and consumption-based procurement. In this episode, Michael Watson is joined by Dan Entrup (Founder of Agnowledge) and Freeman Lewin (Founder of BrickRoad) to bridge the gap between institutional data strategy and the emerging ML data marketplace. The conversation explores why the "data-…

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  • Expert Network Technology & AI | Daniel Entrup

    September 05, 2025 · 📺 Curiosity Code Podcast

    AI is transforming expert networks—but the human element still defines success. Daniel Entrup, expert network veteran and strategist, reveals what technology can't replace and how to build trust-driven marketplaces that blend automation with relationship management. From fraud prevention to AI coaching for analysts, this episode explores the invisible infrastructure behind professional knowledge sharing. Learn why early automation failed, how data gaps hold back AI adoption, and which use cases will reshape the industry in the next 5 years. 📍 KEY TOPICS & TIMESTAMPS 0:00 Introduction 3:26 Da…

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  • 01 - The Dan Entrup Episode

    April 06, 2023 · 📺 I See Data People

    Our co-hosts Evan Schnidman and Omri Shtayer interview Dan Entrup. Dan is currently the Executive Director of Data Strategy at Henry Schein, and was previously the Director of Partnerships at FactSet, after having been the CEO of Datavore and head of strategy at M Science. Dan began his career in the expert network side of the industry, so he deeply understands how people are central to the data industry. Our discussion revolves around understanding your client base, human capital analytics, understanding how different organizations use data, and how to price data properly for differing us…

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The summary and quote tags on this profile are produced with AI assistance from verified, first-person interview transcripts, then checked by our team to confirm the speaker's identity and the accuracy of every quote. See how we verify →