Collaboration

Seamlessly share progress across projects

Manage team projects with a lightweight system of record. It's easy to hand off projects when every experiment is automatically well documented and saved centrally.

Reproduce results

Effortlessly capture configurations

With Weights & Biases experiment tracking, your team can standardize tracking for experiments and capture hyperparameters, metrics, input data, and the exact code version that trained each model.

Debug ML models

Identify performance issues quickly

Focus your team on the hard machine learning problems, and let Weights & Biases take care of the legwork of tracking and visualizing performance metrics, example predictions, and even system metrics to identify performance issues.

Transparency

Share updates across your organization

It's never been easier to share project updates. Explain how your model works, show graphs of how  model versions improved, discuss bugs, and demonstrate progress towards milestones.

Central dashboard

A system of record for your model results

Add a few lines to your script, and each time you train a new version of your model, you'll see a new experiment stream live to your dashboard.

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Hyperparameter sweeps

Try dozens of model versions quickly

Optimize models with our massively scalable hyperparameter search tool. Sweeps are lightweight, fast to set up, and plug in to your existing infrastructure for running models.

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Artifact tracking

Lightweight model and dataset versioning

Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation.

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Interactive reports

Explore results and share findings

It's never been easier to share project updates. Explain how your model works, show graphs of how  model versions improved, discuss bugs, and demonstrate progress towards milestones.

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Governance

Protect and manage valuable IP

Use this central platform to reliably track all your organization's machine learning models, from experimentation to production. Centrally manage access controls and artifact audit logs, with a complete model history that enables traceable model results.

Data provenance

Reliable records for auditing models

Capture all the inputs, transformations, and systems involved in building a production model. Safeguard valuable intellectual property with all the necessary context to understand and build upon models, even after team members leave.

Organizational efficiency

Unlock productivity, accelerate research

With a well integrated pipeline, your machine learning teams move quickly and build valuable models in less time. Use Weights & Biases to empower your team to share insights and build models faster.

Data security

Install in private cloud and on-prem

Data security is a cornerstone of our machine learning platform. We support enterprise installations in private cloud and on-prem clusters, and plug in easily with other enterprise-grade tools in your machine learning workflow.

Access the white paper

Peruse our findings on how building the right technical stack for your machine learning team supports core business efforts and safeguards IP.
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