XIVO runs at 140FPS on stored data (here from a RealSense D435i sensor) or on live streams with latency of around 1-7ms, depending on the hardware. It takes as input video frames from a calibrated camera and inertial measurements from an IMU, and outputs a sparse point cloud with attribute features and 6 DOF pose of the camera. It performs auto-calibration of the relative pose between the camera and the IMU as well as the time-stamp alignment. More demos are available here, the aproach is described in this paper. XIVO does not perform post-mortem refinement (bundle adjustment, pose graph optimization), but that can be easily added as post-processing. XIVO is an open-source repository for visual-inertial odometry/mapping. It is a simplified version of Corvis [Jones et al.,Tsotsos et al.], designed for pedagogical purposes, and incorporates odometry (relative motion of the sensor platform), local mapping (pose relative to a reference frame of the oldest visible features), and global mapping (pose relative to a global frame, including loop-closure and global re-localization — this feature, present in Corvis, is not yet incorporated in XIVO).