A new integration between Encord and Weights & Biases allows seamless synchronization of annotation data across both platforms, eliminating the need for manual data exports or complex engineering. With this integration, updates in Encord are automatically reflected in Weights & Biases as versioned Artifacts, ensuring that training datasets are always aligned with the latest ground truth labels. This process enhances model iteration speed, reduces label drift, and bridges data and model workflows by enabling Encord to serve as the source of truth for labeled data, while Weights & Biases manages training and experiment records. The integration simplifies data management, reduces engineering efforts, and supports operational visibility, allowing teams to focus on improving model performance and debugging data-centric issues effectively. Additionally, it facilitates the management of human feedback and rubric evaluations, which can be analyzed alongside quantitative metrics in Weights & Biases.