To contribute to the evolution of spacecraft operations, Neuraspace aims to solve the space debris problem by protecting satellites operators from the losses caused by collisions, liabilities from leaving debris in orbit, and allowing insurance companies to better price the risk that each satellite poses. The continuous increase in space traffic and debris in the last years lead to a significant increase in the amount of information related to conjunction events. This situation poses a very complex challenge to space operators as the conjunction events need a careful “manual'' analysis, which is time, cost and effort consuming. AI (specifically ML) algorithms represent an essential technique in the automation of this process, mainly due to their ability to handle big amounts of data. By using a data-driven approach with state-of-the-art Machine Learning techniques, Neuraspace is able to outperform the current methods, while automating the process of collision risk avoidance. Neuraspace enables the timely detection of up to 33% more high-risk collisions that have been so far undetected, thus securing space operations.