AI Data Annotation and Training Services

We deliver precise bounding boxes, semantic segmentation, polygon annotations, keypoint labeling, and object tracking across image and video datasets. Whether you are training a computer vision model for autonomous systems, retail, or medical imaging, our annotators handle complex visual data with accuracy and speed.

Our text annotation services cover intent classification, entity recognition, sentiment tagging, coreference resolution, and dialogue act labeling. We work with multilingual datasets and domain-specific corpora so your NLP models understand real language in context, not just clean benchmark samples.

We transcribe, timestamp, and label audio datasets for speech recognition, speaker identification, emotion detection, and voice command training. Our annotators are trained to handle accents, background noise, and overlapping speech patterns that matter most for production model performance.

For autonomous vehicles, robotics, and spatial computing applications, we provide 3D bounding box labeling, lane marking annotation, and object classification across LiDAR and point cloud datasets. Precision here is critical, and our workflows reflect that standard.

We support Reinforcement Learning from Human Feedback pipelines by providing preference ranking, response comparison labeling, and model output evaluation. This service is designed for teams fine-tuning large language models or building custom AI assistants that require human judgment at scale.