How Custom Workflows, Real Time Functionality And Predictive AI Decrease Time-To-Value And Increase ROI In Data Enrichment


The age-old adage "time is money" is perhaps more applicable today than during anytime in history. In this presentation, iMerit deep learning engineer Hrishikesh Hippalgaonkar talks about how a transformational, solutions-oriented approach to addressing data labeling problems will decrease Time-to-Value and increase ROI in the Artificial Intelligence and Machine Learning ecosystems. He will speak specifically of solutions mapping to custom workflows, real-time functionalities and predictive AI and how these solutions factor into the data labeling pipeline for AI and Machine Learning. He discusses the need for taking a holistic, solutions-based approach to AI deployments, and why partnering with organizations with vision and the ability to execute at scale are critical to AI success.


iMerit Deep Learning Engineer Hrishikesh Hippalgaonkar, has a MS from USC in Electrical Engineering, with a concentration in Computer Vision and Deep Learning technology. He has a BE in Electronics and Telecommunications from the University of Pune. Before iMerit, Hippalgaonkar was on the teams at Frenzy AI and DreamVu.

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