List of Weights and Biases Customers
San Francisco, 94110, CA,
United States
Since 2010, our global team of researchers has been studying Weights and Biases customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Weights and Biases for AI infrastructure from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Weights and Biases for AI infrastructure include: Siemens, a Germany based Manufacturing organisation with 312000 employees and revenues of $84.55 billion, OpenAI, a United States based Professional Services organisation with 5328 employees and revenues of $3.70 billion, Woven by Toyota, a Japan based Automotive organisation with 2212 employees and revenues of $500.0 million and many others.
Contact us if you need a completed and verified list of companies using Weights and Biases, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Weights and Biases customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
|---|---|---|---|---|---|---|---|---|---|---|---|
 |
OpenAI | Professional Services | 5328 | $3.7B | United States | Weights and Biases | Weights and Biases | AI infrastructure | 2020 | n/a |
In 2020, OpenAI's Robotics team adopted Weights and Biases as a core component of its AI infrastructure. The implementation targeted AI/ML research and robotics R&D in the United States, with Weights and Biases serving as the centralized platform for experiment tracking and structured reporting within the team.
The deployment emphasized W&B Reports as the primary mechanism to document, share, and monitor large-scale experiment runs, and used experiment tracking to capture run metadata, metrics, and artifacts. Weights and Biases Reports were used to assemble reproducible experiment narratives and persistent experiment records that combine visualizations and logs for cross-project collaboration.
Rollout to the Robotics group transitioned over roughly six months, during which Reports became the team’s primary method for sharing results and coordinating work. The adoption formalized report-centric workflows, improving experiment collaboration and reproducibility across large projects.
|
 |
Siemens | Manufacturing | 312000 | $84.5B | Germany | Weights and Biases | Weights and Biases | AI infrastructure | 2023 | n/a |
In 2023, Siemens implemented Weights and Biases as part of its AI infrastructure for robotics, warehouse automation, and computer vision work in Germany. Weights and Biases is used to instrument experiment tracking, comparisons, and model development pipelines for warehouse robot AI, establishing a central record for experiments and metrics.
The implementation centered on experiment tracking and metric dashboards, with explicit use of artifact versioning and experiment tables to capture model inputs, training runs, and evaluation metrics. This configuration supports reproducible model development workflows and comparative analyses across model variants, enabling standardized experiment metadata and lineage capture.
Deployment was focused on embedding Weights and Biases into existing model development pipelines used by Siemens teams working on industrial AI for warehouses, providing a single source for run history and model artifacts. Operational coverage emphasized engineering and ML development functions collaborating on robotics and computer vision projects in Germany, where teams use the platform to validate model iterations and share results across stakeholders.
Governance outcomes included improved pipeline traceability and stronger experiment governance, with reported productivity gains and greater confidence in model lineage and auditability. The implementation reinforced reproducibility and experiment comparability without referencing specific upstream systems, preserving a clear separation between model development tooling and operational control processes.
|
 |
Woven by Toyota | Automotive | 2212 | $500M | Japan | Weights and Biases | Weights and Biases | AI infrastructure | 2022 | n/a |
In 2022, Woven by Toyota deployed Weights and Biases as AI infrastructure to centralize experiment tracking and dataset curation for its autonomous driving ML R&D operations in Japan. Weights and Biases functions as the central system of record for experiments, autolabeling and continuous learning workflows, consolidating experiment metadata and dataset artifacts to support iterative model development.
The implementation leverages Experiments, Sweeps, Tables and Plans, with explicit integration of Launch and the Model Registry to enable model lifecycle coordination and model-management practices. Configuration focused on experiment provenance, dataset versioning, autolabel pipelines and sweep-driven hyperparameter searches to standardize repeatable training and evaluation workflows.
Integrations emphasize dataset curation and autolabeling pipelines, plus orchestration between experiment tracking and model-management modules to accelerate continuous training and deployment loops. Operational coverage is concentrated on Woven by Toyota's autonomous driving ML R&D teams in Japan, where Weights and Biases is used to unify experiment artifacts and reporting across research and engineering functions.
Governance work established Weights and Biases as the authoritative experiment and model record, standardizing reporting workflows and provenance capture for experiments and datasets. The deployment is reported to accelerate continuous learning workflows, with a cited 10x velocity improvement in some processes.
|
Buyer Intent: Companies Evaluating Weights and Biases
- DKSH Holding, a Switzerland based Professional Services organization with 29699 Employees
- NextRow Digital, a United States based Professional Services company with 150 Employees
- Columbia University, a United States based Education organization with 21489 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||