Super-LIO is a LiDAR-Inertial Odometry (LIO) system implemented as a ROS2 application. It fuses IMU and LiDAR data using an Error-State Kalman Filter (ESKF) for state estimation and a novel OctVoxMap for efficient point cloud mapping and nearest-neighbor search. The system supports multiple LiDAR types (Livox, Hesai, Velodyne, Ouster, NCLT) and includes a relocation mode using pre-built maps with ICP/NDT initialization. The architecture is a monolithic ROS2 node with a state machine (KF initialization, map initialization, then continuous processing). Key data flows: IMU propagation, LiDAR scan motion undistortion, downsampling, point-to-plane residual optimization, map update, and odometry publication. The codebase demonstrates strong engineering with C++20, TBB parallelism, and well-structured Lie group math (SO3, SE3, S2) in a separate 'basic' library. The OctVoxMap component is a standout contribution with precomputed search orders for fast KNN queries.