MLOps & Tooling Private

Weights & Biases

ML experiment tracking and model management

Founded 2017 San Francisco, CA 300+ employees Series C ($200M raised) Freemium + Enterprise
Funding Status
Series C ($200M raised)
Private Company

About Weights & Biases

Weights & Biases (W&B) is the leading ML experiment tracking and model management platform, used by over 1,000 enterprise teams and most of the world's top AI research labs. Founded in 2017 by Lukas Biewald, Chris Van Pelt, and Shawn Lewis, W&B provides the tools that ML engineers use to track experiments, visualize training runs, manage datasets, and collaborate on model development.

W&B is to machine learning what GitHub is to software development — the system of record for ML work. Every major AI lab (OpenAI, DeepMind, Meta AI, Anthropic) and thousands of companies use W&B to track their model training experiments. The platform has tracked over 1 billion ML experiments.

The company's expansion into LLM evaluation (Weave) and prompt management reflects the shift from traditional ML to generative AI, while maintaining its core strength in experiment tracking and model management.

Products & Services

W&B Experiments

ML experiment tracking with automatic logging, visualization, and comparison. The industry standard for tracking training runs.

Platform

W&B Models

Model registry and management. Version, stage, and deploy models with full lineage tracking.

Platform

W&B Weave

LLM evaluation and observability platform. Track, evaluate, and improve generative AI applications.

LLM Tooling

W&B Sweeps

Automated hyperparameter tuning. Run distributed parameter searches with Bayesian optimization.

ML Tool

Leadership

L
Lukas Biewald
Co-Founder & CEO
Previously founded CrowdFlower (now Figure Eight), a data labeling company.

Notable Achievements

  • Used by OpenAI, DeepMind, Meta AI, and virtually every major AI lab
  • Tracked over 1 billion ML experiments
  • Industry standard for ML experiment tracking
  • Raised $200M at $1.25B valuation
  • Expanding into LLM evaluation with Weave platform

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