Pre-Trial manages bond information in a case management system which could be a vendor-the provided system, statewide system, or home-grown system. These systems typically output some reporting which provides basic information about the number of bonds issued, types of bonds issued, etc. The purpose of the report is to make sense of the bond data and is also generated for annual reporting purposes. This is how Pre-Trial is used to look at their data and make sense of it.However, with the recent arrival of machine learning and Artificial Intelligence, a fundamental shift needs to take place regarding how we look at historical Pre-Trial data (we will use sample bond data in this white paper) to discern more than what Pre-Trial is used to. We will examine in this white paper how AI/Machine Learning can be put to use for better outcomes for Pre-Trial.

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