We annotate text, image, video, audio, and other data sources, so that data is recognizable to computer systems programmed for supervised-learning.
Train models to understand both content and context
Teach models to recognize individuals, objects, and environments with image and video annotation
Data Collection, Data cleaning, Synthetic data set creation, Robustness and Adversarial attack, Deepfake Detection
Text, image, video, audio, and other data sources annotations
Evaluate a trained model on test data set
We train models to respond to the occurrence of exceptions