Robotics and Physical AI systems rely heavily on accurately labeled, multimodal datasets, which are crucial for ensuring safety and robust model performance in applications like drones, robotics, and autonomous vehicles. These datasets encompass diverse data types such as LiDAR, radar, 3D point clouds, video, and audio sensors. Various platforms have emerged to meet these data labeling needs, each with unique features and strengths. Encord is highlighted as a comprehensive solution due to its support for a wide array of modalities and advanced features such as workflow orchestration, quality assurance, and compliance, making it particularly suitable for enterprise-scale robotics projects. Other platforms, like Segments.ai and Scale AI, offer specialized capabilities for LiDAR-camera fusion and perception data pipelines, while CVAT provides flexibility through open-source customization. Each platform caters to different robotics needs, from large-scale operations to lightweight startups and high-security environments.