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The Missing Puzzle Piece in Agentic Financial Analysis: Self-Learning Knowledge Graphs

Session Track: Data Science

Session Time:

Session description

Finance is the final frontier for agentic frameworks in production. With ever-changing global markets, the biggest problem for agentic financial analysts is generating actionable insights from vast amounts of data. Many tools merely regurgitate or summarize information, offering limited practical value. In this session, Mitesh and Enzo will explain how self-learning knowledge graphs are revolutionizing financial analysis by replicating the dynamic mental models used by investment professionals. You will leave with a glimpse of the future of finance, powered by self-learning knowledge graphs, and gain a deep understanding of best practices in building agentic financial analysts that generate real-time insights, transforming data into actionable intelligence.

Speaker

photo of Mitesh Tank

Mitesh Tank

Founder & CEO, Datapher AI

Mitesh Tank, founder of Datapher AI – an agentic financial analyst that helps investment professionals make better informed. With over twenty years in financial technology and portfolio management, across three continents, he developed equity strategies, led index research at Marshall Wace, and managed portfolios at State Street Global Advisors. He has also helped endowment funds invest in emerging markets and aided in application development of global prime brokerage technology platforms at Nomura and Lehman Brothers. He holds an MBA from Duke University and a Bachelor of Engineering from The Maharaja Sayajirao University of Baroda. He enjoys long-distance running and global cinema.