Weights & Biases

Weights & Biases: The AI Developer Platform"

Weights & Biases (W&B) is an AI developer platform designed to help teams build, train, validate, deploy, and monitor AI agents, models, and applications with confidence. It provides an integrated suite of tools for experiments tracking, reproducibility, model registry, data visualization, automation, and collaborative workflows. The platform emphasizes observability, MLOps best practices, and seamless integration with popular ML frameworks to accelerate AI development from experimentation to production.

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How it works

1. Track experiments and runs. Log hyperparameters, metrics, artifacts, and lineage across ML experiments to compare runs and reproduce results.
2. Visualize and explore data. Inspect tables, charts, and dashboards to gain insights into models, datasets, and performance.
3. Manage models and datasets. Use a centralized registry to version, share, and deploy models and datasets across teams.
4. Automate workflows. Set up sweeps, pipelines, and integrations to automate ML workflows and trigger actions based on events.
5. Build agentic AI applications. Leverage Weave to compose LLMs, tools, and prompts into autonomous or semi-autonomous AI applications with guardrails and monitoring.

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Core Use Cases

• Build and monitor AI agents and autonomous workflows
• Track and compare ML experiments and hyperparameter sweeps
• Manage model and dataset versions across the lifecycle
• Visualize training metrics, data distributions, and model performance
• Integrate with popular ML libraries and frameworks (LangChain, LlamaIndex, PyTorch, Transformers, Scikit-Learn, XGBoost, etc.)
• Deploy and monitor production ML systems with observability and guardrails
• Collaborate across teams with shared dashboards, reports, and artifacts

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How to Use Weights & Biases

• Install and initialize: import wandb; wandb.init(project="my-project");
• Log data: wandb.log({"loss": loss, "accuracy": acc});
• Save artifacts: wandb.log_artifact("model.pt", type="model");
• Create and run sweeps for hyperparameter optimization
• Publish models and datasets to the registry for reuse
• Build dashboards and reports to communicate results

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Weave: Build Agentic AI Applications

• Weave is an integrated workflow layer to compose LLMs, prompts, tools, and retrieval into agentic pipelines.
• Examples include tracing LLM calls, documenting retrieval steps, and monitoring agent behavior.
• Supports quickstart examples for LangChain, LLamaIndex, OpenAI, and other integrations.

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Integrations and SDKs

• Works with popular tools and frameworks (LangChain, LlamaIndex, PyTorch, TensorFlow, Scikit-Learn, XGBoost, Transformers, OpenAI, etc.).
• Provides examples and snippets to accelerate integration into existing codebases.
• Supports multiple deployment options (SaaS, dedicated/enterprise, customer-managed cloud providers).

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Safety and Governance

• Observability features help detect anomalies, outliers, and drift in production models.
• Guardrails and monitoring capabilities for responsible AI practices and compliance needs.

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Core Features

• Experiment tracking and run metadata logging
• Hyperparameter sweeps and optimization (Sweeps)
• Tables and dashboards for data visualization and analysis
• Centralized registry for models, datasets, prompts, code, and artifacts
• Reproducibility: track artifacts, versions, and lineage
• Automated workflows and integrations (automations, triggers)
• Agentic AI tooling via Weave for building AI agents and pipelines
• Observability and guardrails for production ML systems
• Collaborative reports and dashboards to share results across teams
• Flexible deployment options: SaaS, dedicated, or customer-managed cloud

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Target Users

• Data scientists and ML engineers building and evaluating models
• AI researchers conducting experiments and benchmarks
• ML engineers deploying and monitoring production models
• Teams building AI agents, tools, and autonomous workflows

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Pricing and Plans

• (Refer to the official site for current pricing and enterprise options.)

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Disclaimer

• This overview describes general capabilities of the Weights & Biases AI developer platform and its Weave integration for building and monitoring AI applications.