Weights & Biases

Weights & Biases (W&B) is a leading machine learning experiment tracking and model management platform that has expanded its capabilities to include governance-relevant features for organizations seeking to maintain oversight of their AI development processes. Founded in 2017 and headquartered in San Francisco, California, W&B has become one of the most widely adopted MLOps tools in the industry, used by thousands of organizations ranging from academic research labs to Fortune 500 enterprises. The platform's core strength lies in its experiment tracking capabilities, which automatically capture and organize every aspect of ML experimentation including hyperparameters, metrics, model artifacts, code versions, and dataset references. This comprehensive tracking creates a detailed audit trail of model development that is invaluable for governance and compliance purposes. W&B's model registry provides version-controlled model management with metadata tracking, approval workflows, and lineage documentation that supports governance requirements around model documentation and traceability. W&B Reports enable teams to create rich, interactive documents that combine visualizations, analysis, and narrative context, making it easier to communicate model development decisions to governance stakeholders. The platform's collaborative features facilitate review processes and knowledge sharing across data science and governance teams. W&B also provides tools for dataset versioning and visualization, supporting data governance requirements that underpin responsible AI development. The platform offers a freemium pricing model with a generous free tier for individuals and small teams, along with team and enterprise plans that add collaboration features, access controls, and dedicated support. This accessibility has contributed to W&B's widespread adoption across the ML community. The platform integrates with virtually every major ML framework and cloud provider, making it a natural fit for diverse technology stacks. However, it is important to recognize that W&B's governance features are secondary to its primary mission as an experiment tracking and MLOps platform. Organizations requiring dedicated AI governance capabilities such as regulatory compliance mapping, policy management, risk assessment frameworks, or automated compliance reporting will likely need to supplement W&B with purpose-built governance tools. For teams already using W&B for experiment tracking, its governance-relevant features provide a valuable foundation upon which more comprehensive governance processes can be built.