W&B Weave
Trace, evaluate, and monitor LLM applications systematically
W&B Weave is profiled here as a Prompt Management tool for engineering teams. Read about features, pricing, and how it compares to related options in the tools directory.
Description
Weave is the LLM evaluation and observability toolkit from Weights & Biases, the ML developer platform founded by Lukas Biewald, Chris Van Pelt, and Shawn Lewis and acquired by CoreWeave in 2025. A single decorator traces every function and model call, links the traces to versioned datasets and scorers, and turns those pieces into repeatable evaluations that quantify each prompt or model change. Weave shares an account with W&B Models, so teams already tracking training experiments extend the same workspace to LLM application work.
Key Capabilities:
Call tracing with automatic input, output, and code versioning
Evaluation framework with custom scorers and LLM-as-judge support
Dataset versioning for reproducible test sets
Playground for side-by-side model and prompt comparison
Online monitors and guardrail scorers for production traffic
Python and TypeScript SDKs with OpenTelemetry compatibility
Alternative tools
- Traceloop
OpenTelemetry-native tracing for LLM applications
- LangChain
The standard open-source framework for LLM applications
- Portkey
AI gateway with routing, guardrails, and prompt management
- Freeplay
Prompt management, evals, and observability for product teams
- DSPy
Declarative framework for programming and optimizing LLM pipelines
- MLflow
Track experiments, manage models, and evaluate LLM applications across the full ML lifecycle