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Sarah Nagy

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CEO Seek AI

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Generative AI & the Natural Language Interface for Data |  Seek AI

ABOUT THE TALK: With the advancement of AI, the natural language interface for data is more valuable than ever before. This talk explores three key questions. First, what would a natural language interface for data actually look like? Second, what kind of value would it add to organizations using the Modern Data Stack? Third, what will the challenges look like when it comes to working with a natural language interface for data? Sarah Nagy will share real-world learnings from Seek's customers for each of these questions.

ABOUT THE SPEAKER: A former quant, Sarah Nagy founded Seek AI in 2021. Prior to starting Seek, Sarah most recently led the consumer data team at Citadel's Ashler Capital. Prior to joining Citadel, Sarah led the quant arms at two startups, Edison and Predata, which both successfully exited. Sarah started her career as a quant at ITG developing algorithmic trading strategies. Sarah has a Master in Finance degree from Princeton and dual Bachelor's degrees in Astrophysics and Business Economics from UCLA.

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Sarah and Chris are both at the forefront of bringing the promise of gen AI to our actual work as data people—which is a unique challenge!  Precise truth is critical for business questions in a way that it's not for a consumer search query. Sarah Nagy is the CEO of Seek AI, a startup that aims to use natural language processing to change how professionals work with data. Chris Aberger currently leads Numbers Station AI, a startup focused on data-intensive workflow automation. In this conversation with Tristan and Julia, they dive into what this future might actually look like, and tangibly what we can expect from gen AI in the short/medium term. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.  The Analytics Engineering Podcast is sponsored by dbt Labs.