Data Labeling

The process of annotating raw data (text, images, audio) with tags or classifications that teach AI models to recognize patterns. For AI agents, labeled data is used to train intent classifiers, evaluate agent accuracy, fine-tune models for domain-specific tasks, and build evaluation test suites. Modern approaches combine human labelers with AI-assisted labeling (where models pre-label data and humans correct errors), reducing cost by 50–70% versus fully manual annotation.