Weights & Biases is an AI developer platform for tracking, evaluating and debugging machine learning models and LLM applications. Its Weave product traces LLM calls, document retrieval and agent steps from a few lines of Python, while the Models side covers experiments, sweeps, tables, a model registry and artifacts. Evaluations, guardrails and a playground help teams test agents before release, and a mobile iOS app lets engineers watch training runs from anywhere. The company is now part of CoreWeave Forge.
Machine learning engineers, data scientists and AI application developers are the core users. Research teams use it to compare training runs, product teams use it to monitor LLM quality in production, and enterprise security groups can rely on its ISO 27001, SOC 2 and HIPAA compliance, with multi-tenant and dedicated deployment options. Python skills are expected, since integration happens through an SDK and decorators. It fits solo researchers as well as larger organizations running many experiments at once.
Typical workflows include logging hyperparameters and metrics during PyTorch or TensorFlow training, running sweeps to find better settings, and versioning datasets and models in a registry. For LLM apps, developers add tracing to see every prompt, tool call and retrieval step, then run evaluations to catch regressions after a prompt or model change. Integrations with LangChain, LlamaIndex, Hugging Face Transformers, Lightning, Keras, scikit-learn and XGBoost mean existing code needs little change. Teams share findings through reports and trigger actions with automations. Because the company is now part of CoreWeave Forge, some training and inference capabilities are described under that brand, and Weave remains the entry point for agent and application work. Compliance with NIST 800-53 and GDPR requirements helps regulated companies adopt it with fewer procurement hurdles.
