Jaxon automates data labeling to create training datasets for AI in minutes, a process that humans currently take months to do by hand. AI requires training data because machines cannot ‘read’ natural language like humans do and require labeled data to ‘learn’ new concepts, contexts, and domain-specific terminology. The best training datasets come from an organization’s own data, and massive efforts are underway to label that data for accurate training. Hand-labeling this data is the biggest bottleneck in building AI as human labelers are slow, expensive, and inconsistent. Jaxon eliminates this bottleneck by automating the process of labeling data, allowing data science teams to build fully-trained models in days vs months.