RAIC Labs
Daniel S. is a seasoned professional with extensive experience in leadership and strategic roles within both military and civilian sectors. Currently serving as a Federal Account Executive and Microsoft Alliance Manager at RAIC Labs since September 2023, Daniel has held various significant positions including Board Advisor at NAX Group and Adjunct Professor at Davis Defense Group, Inc. Previously, Daniel worked as a Mission Account Executive at Microsoft, focusing on digital transformation initiatives for the Department of the Navy. Daniel's military background includes high-level roles with the United States Marine Corps, where responsibilities encompassed program and project management across multiple teams and geographical locations. Daniel holds a Master's degree in Administrative Leadership from the University of Oklahoma and a Bachelor's degree in Mathematics from the University of Wisconsin-Eau Claire.
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RAIC Labs
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We've rebranded, Synthetaic is now RAIC Labs! Quickly derive insights from large, unlabeled geospatial, video, and image datasets without time-intensive human labeling or pre-built models. Rapid Automatic Image Categorization (RAIC) is an unbiased tool that meets users’ ever-changing analytic demands for their perpetually evolving datasets, in an unrivaled timeline. RAIC enables users to find and classify anything in minutes, not months, without labeled data. Simply provide a single example object image and RAIC will find similar objects in your unlabeled dataset and return contextually-related results. You can then improve the AI by identifying the best results through an intuitive human nudge tool. From there, you can run inference jobs and turn results into insights using dashboarding tools or existing analytics platforms.