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Advances in gene editing, cellular biology, stem cells, robotic experiments, and more have allowed scientists to manipulate biology in previously unheard-of ways. A leading life sciences company was struggling to accelerate their AI journey including the need to analyze complex, large -scale data sets and was facing bottlenecks due to human observation.
We collaborated with the customer to create an end-to-end solution that focused on keeping machine learning models at its core. We trained the model on past exception data to help its resolutions determine if an exception is being recorded accurately. We also ensured that the solution allowed room for automation to reduce the amount of manual effort in the process as the solution could reduce false exceptions by as much as 80%.
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