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Weave: LLMOps
Traces
Explore and debug AI applications
Evaluations
Rigorous evaluations of AI applications
Agents
Observability tools for agentic systems
Guardrails
Block prompt attacks and harmful outputs
Models: MLOps
Experiments
Track and visualize your ML experiments
Sweeps
Optimize your hyperparameters
Tables
Visualize and explore your ML data
Core Platform Features
Registry
Publish and share your ML models and datasets
Artifacts
Version and manage your ML pipelines
Reports
Visualize and explore your ML data
SDK
Log ML experiments and artifacts at scale
Automations
Trigger workflows automatically
Solutions
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Use Cases
Train LLMs
Fine-tune LLMs
Computer Vision
Time Series
Recommender Systems
Classification & Regression
Train LLMs
Fine-tune LLMs
Computer Vision
Time Series
Recommender Systems
Classification & Regression
Industries
Autonomous Vehicles
Communications
Financial Services
Healthcare & Life Sciences
Public Sector
Scientific Research
Autonomous Vehicles
Communications
Financial Services
Healthcare & Life Sciences
Public Sector
Scientific Research
Case Studies
Canva
Learn how Canva leverages W&B to deploy models
Microsoft
Learn how Microsoft uses W&B for their ML projects
Toyota
Learn how Toyota uses W&B for autonomous driving
OpenAI
Learn how OpenAI Robotics uses W&B for large scale ML
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Enterprise
(Multi-tenant SaaS)
Multi-tenant and scalable, fully-managed SaaS infrastructure in GCP, providing economies of scale and simpler setup.
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Autoscaling multi-tenant infra in GCP
Economies of scale
No Infra and SRE overhead
Shared VPC and IAM
Shared metadata and data storage
Per-team Secure Storage Connector
SSO and RBAC
Managed support at scale, and more
Autoscaling multi-tenant infra in GCP
Economies of scale
No Infra and SRE overhead
Shared VPC and IAM
Shared metadata and data storage
Per-team Secure Storage Connector
Connect securely to the data in your own cloud blob storage
SSO and RBAC
Managed support at scale, and more
Most secure with global infrastructure
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Dedicated
(Single-tenant SaaS)
Single-tenant and isolated, fully-managed SaaS in the cloud and region of customer’s choice, with required governance capabilities.
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Choice of cloud (AWS, GCP, Azure) and region
No Infra and SRE overhead
Per-deployment VPC and IAM
Per-deployment metadata and data storage
Per-deployment and Per-team Secure Storage Connector
SSO and RBAC
Audit logs
Advanced security options
Deployment size per usage
Dedicated support channel, and more
Choice of cloud (AWS, GCP, Azure) and region
No Infra and SRE overhead
Per-deployment VPC and IAM
Per-deployment metadata and data storage
Per-deployment and Per-team Secure Storage Connector
SSO and RBAC
Audit logs
Advanced security options
Deployment size per usage
Dedicated support channel, and more
Most appropriate for non-cloud and air-gapped
Customer managed
(Self-hosted)
Single-tenant deployment in customer-managed environment for maximum control by customer infra and SRE teams.
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Deploy in your infrastructure
Best suited for Kubernetes outside AWS, GCP and Azure
Requires its own database
Fully managed by your Infra and SRE team
SSO and RBAC
Audit logs
Advanced security options
Requires minimum annual commitment
Deploy in your infrastructure
Best suited for Kubernetes outside AWS, GCP and Azure
Requires its own database
Fully managed by your Infra and SRE team
SSO and RBAC
Audit logs
Advanced security options
Requires minimum annual commitment
Platform
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Experiments
Lightweight experiment tracking
Reports
Collaborative dashboards
Artifacts
Dataset and model versioning
Tables
Interactive data visualization
Sweeps
Hyperparameter optimization
Models
Centralized model registry
Launch
Automated ML workflows
Prompts
LLMOps and prompt engineering
Monitoring
Observability for production ML
Weave
Interactive ML app builder
Solutions
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