It's never been easier to wrangle and extract value from huge data… but how should a startup think about getting value from data streams that are just getting started, or find insights about small partitions of data for individual customers?I'll present on how we've tackled these challenges at frame.ai, where we're focused on providing realtime insights about realtime chat streams within one company at a time. I'll talk about setting metrics focused on time-to-value for customers, leveraging model stacks trained on larger data sets, and adopting NLP analysis techniques that behave well where data is sparse.
George is co-founder and CEO of frame.ai, a conversational commerce startup focused on helping humans talk business more efficiently. Previously, George was Head of Adaptive Learning at Knewton, where he oversaw a data and engineering team driving educational experiences for 10MM students around the world. In past lives, George ran a hedge fund, implemented genomic analysis pipelines, and kept tabs on thousands of container ships to earn his PhD at Carnegie Mellon.
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