Online monitoring is an architectural pattern well-known to safety engineers, but it had to be adapted to AI technologies. In this paper, an innovative multi-time scale online monitoring architecture is presented. The main idea is to combine several monitoring timescales - Present- Time Monitoring (PTM), Near-Past Monitoring (NPM), and Near-Future Monitoring (NFM) - on different monitoring assets (inputs, internal states, and outputs of the AI model) to ensure a high anomaly detection rate by design of the online monitor.