In a growing software company, the most important project knowledge rarely lives in one place. Architecture decisions sit in code repositories. Team information is stored elsewhere. Budgets live in Drive. Delivery context is spread across project tools, documents, and conversations. Some of the most useful information may never be written down at all. The result […]

Using a machine learning model with image processing and deep learning to classify embryos into groups for better pregnancy success prediction.

Achieving a 15% decrease in carbon footprint and energy consumption costs by creating an optimization algorithm for charging electric vehicles.