AI visibility report for Weights & Biases in AI/ML Infrastructure & LLM Tools.

Weights & Biases (W&B) is an AI developer platform founded in 2017 in San Francisco by Lukas Biewald, Chris Van Pelt, and Shawn Lewis. The platform provides two primary product lines: W&B Models, covering ML experiment tracking, hyperparameter optimization, artifact versioning, and a centralized model registry; and W&B Weave, a toolkit for tracing, evaluating, and monitoring LLM applications and AI agents. A newer W&B Training product supports serverless reinforcement learning and supervised fine-tuning for LLMs. W&B Inference offers a hosted open-source model API. The platform is used by over 1,400 organizations—including OpenAI, Meta, NVIDIA, Microsoft, AstraZeneca, Toyota, and Canva—and by more than 1 million AI engineers. In May 2025, CoreWeave completed its acquisition of the company for a reported $1.7 billion.

Weights & Biases is an end-to-end AI developer platform spanning ML model development (experiment tracking, hyperparameter sweeps, artifact versioning, model registry) and LLM/GenAI application development (tracing, evaluation, guardrails, agent monitoring via W&B Weave), plus serverless LLM fine-tuning and hosted open-source model inference. Now a subsidiary of CoreWeave.