Weights & Biases

Weights & Biases: the AI developer platform. Build better models faster, fine-tune LLMs, develop GenAI applications with confidence, all in one system of record developers are excited to use. W&B Models is the MLOps solution used by foundation model builders and enterprises who are training, fine-tuning, and deploying models into production. W&B Weave is the LLMOps solution for software developers who want a lightweight but powerful toolset to help them track and evaluate LLM applications. Weights & Biases is trusted by over a 1,000 companies to productionize AI at scale including teams at OpenAI, Meta, NVIDIA, Cohere, Toyota, Square, Salesforce, and Microsoft. Sign up for a 30-day free trial today at http://wandb.me/trial.

Agent Operations

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Founded

2017

Location

San Francisco, CA

Employees

311

Funding

$250M+

Weights & Biases (W&B) Dossier

Overview

**Weights & Biases (W&B)** is an AI developer platform for training, fine‑tuning, evaluating, and shipping machine learning models and AI agents. Founded in 2017 by Lukas Biewald, Chris Van Pelt, and Shawn Lewis, W&B serves 900,000+ users across 1,000+ companies, including teams at OpenAI, Meta, NVIDIA, Cohere, Toyota, Square, Salesforce, and Microsoft. Headquarters: 400 Alabama St, San Francisco, CA.

Explore the platform: [W&B Home](https://wandb.ai/site/)

Customers and proof: [Notable Customers](https://wandb.ai/site/customers/)

Company background: [About W&B](https://wandb.ai/site/company/about-us/)

In May 2025, W&B was acquired by CoreWeave and continues operating and building its AI developer platform under the new ownership.

Acquisition details: [CoreWeave Press Release](https://www.prnewswire.com/news-releases/coreweave-completes-acquisition-of-weights--biases-302445966.html), [CoreWeave Blog](https://www.coreweave.com/blog/coreweave-completes-acquisition-of-weights-biases), [W&B Announcement](https://wandb.ai/wandb_fc/cw-announcement/reports/Weights-Biases-completes-acquisition-by-CoreWeave--VmlldzoxMjU4MzE5OQ)

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Platform Pillars

### 1) W&B Models (MLOps)

End‑to‑end experiment management and reproducibility for traditional ML and deep learning.

Experiment Tracking: Log metrics, compare runs, and visualize training progress.

Artifacts: Version datasets, models, and files to ensure lineage and reproducibility.

Model Registry: Promote models across stages with approvals and history.

Sweeps: Scale hyperparameter tuning and compare results side‑by‑side.

Tables: High‑dimensional data exploration, filtering, and analysis .

Reports: Share results with interactive, team‑ready documentation.

Launch: Reproducible execution for jobs and pipelines.

Learn more: [W&B Platform](https://wandb.ai/site/)

### 2) W&B Weave (LLMOps and Agent Observability)

Purpose‑built for LLM apps and agents, with tracing, evaluation, and governance.

Overview and docs: [Weave Overview](https://wandb.ai/site/weave/), [Weave Docs](https://docs.wandb.ai/weave)

Evaluations and scoring: [Evaluations](https://wandb.ai/site/evaluations/)

Tracing for LLMs/agents: [Traces](https://wandb.ai/site/traces/)

Key capabilities:

Tracing & Timelines: Visualize each step in an agent run—inputs, outputs, tool calls, scores, and system metrics—in a single, navigable timeline.

Evaluations & Scorers: Built‑in and custom scorers for quality, safety, and regression testing; A/B comparisons to pick better prompts or models.

Prompt & Dataset Management: Version prompts, datasets, and results for auditable iteration.

Guardrails: Safety checks and policy enforcement for production deployment.

Cost & Latency Tracking: Monitor token usage and performance to control spend and SLOs.

Agent Framework Integrations: Works with LangChain, LlamaIndex, CrewAI .

More on agents: [Agents Overview](https://site.wandb.ai/agents), [AI Agents Article](https://wandb.ai/site/articles/ai-agents/)

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Who It’s For

ML researchers and engineers running experiments at scale

Data/AI platform teams standardizing MLOps and LLMOps

App teams shipping LLM agents that need tracing, evaluations, and guardrails

Regulated organizations requiring lineage, versioning, and auditability

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Core Use Cases

Experiment tracking with rich charts and shareable reports

Dataset/model lineage via Artifacts and Model Registry

Hyperparameter tuning at scale with Sweeps and clear comparisons

LLM and agent observability with Weave traces and evals

Safety and quality gates using guardrails and scorers

Cross‑team collaboration through Reports, Tables, and alerts

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Integrations

ML frameworks: PyTorch, TensorFlow/Keras, scikit‑learn, JAX

LLM providers and tooling: OpenAI, Anthropic, Cohere, Hugging Face Transformers

Agent frameworks: LangChain, LlamaIndex, CrewAI

Orchestration: Ray/Ray Tune

DevOps & data: GitHub, Slack, Databricks, Snowflake, AWS, GCP, Azure, Kubernetes

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Pricing and Free Trial

W&B offers a free tier and paid plans, plus a 30‑day free trial for teams.

Plans and details: [Pricing](https://wandb.ai/site/pricing/)

Enterprise trial: [30‑Day Trial](https://wandb.ai/site/enterprise-trial/)

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What Users Like

Excellent visualizations and UI for metrics and experiments; easy to compare training runs and datasets .

Fast team onboarding, strong docs, and examples; smoother collaboration than many alternatives .

Artifacts and dataset versioning improve reproducibility in real workflows .

Scalable hyperparameter sweeps with clear, visual comparisons .

Low‑friction Weave traces for LLM monitoring and evaluation .

What to Watch Out For

Pricing can add up for larger teams; self‑hosting for strict compliance may increase total cost .

Performance overhead and slow UI have been reported during heavy runs .

Licensing/self‑hosting and some collaboration limits draw critiques from some users .

Occasional failed runs or UX quirks in larger team settings .

Be mindful of storage costs for large artifacts and media; consider pruning or external storage strategies .

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Quick Facts

Name: **Weights & Biases (W&B)**

Tagline: **The AI developer platform**

Founded: **2017** by Lukas Biewald, Chris Van Pelt, Shawn Lewis

HQ: **400 Alabama St, San Francisco, CA 94110**

Company size: ~311 employees (LinkedIn estimate)

Users/companies: **900,000+ users; 1,000+ companies**

Core products: **Models** (tracking, artifacts, registry, sweeps, tables, reports, launch) and **Weave** (tracing, evaluations, guardrails)

LLM/Agent features: Tracing, evals/scorers, cost/latency tracking, prompt playgrounds, guardrails, agent observability

2025 update: **Acquired by CoreWeave**

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Why It Matters for AI Teams

Consolidates MLOps and LLMOps into a single, auditable workflow—from dataset and model lineage to agent tracing and safety.

Shortens iteration loops through visual debugging, side‑by‑side comparisons, and governed promotion of models/agents.

Improves reliability and compliance with reproducibility, guardrails, and cost/latency observability—critical for production AI.

For deeper exploration, start with the [W&B Platform](https://wandb.ai/site/), [Weave Overview](https://wandb.ai/site/weave/), and [Customers](https://wandb.ai/site/customers/).

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