Practical data services for key AI application scenarios
Different AI scenarios have different requirements for data types, annotation standards, quality control, and delivery timelines.
Data services for language models, multimodal models, and enterprise AI applications, from corpus cleaning to preference annotation and model output evaluation.
Annotation for 2D images, 3D point clouds, lane lines, obstacles, traffic lights, and sensor fusion data for perception and scene understanding.
Data services for object detection, semantic segmentation, pose estimation, defect labeling, and scene understanding for industrial and service robots.
Data classification, image-text matching, style labeling, keyframe annotation, and content review for generative AI and content platforms.
Turning business data into trainable, searchable, and evaluable data assets for enterprise AI systems.
Contact DaoDataAI to discuss your data type, annotation goals, delivery timeline, and quality requirements.