Agent-native tracing
Organizes traces around sessions, turns, steps, tools, and sub-agents, giving developers a view of multi-turn and multi-agent execution.
W&B Weave
Freemium
W&B Weave is an observability and evaluation platform for production AI agents and applications. It helps teams trace agent behavior, evaluate changes, inspect prompts and models, and monitor production interactions.
什么是 W&B Weave？
W&B Weave is an observability and evaluation platform for production AI agents and applications. It helps teams understand how agents behave, measure whether changes improve results, and continue refining systems after deployment.
Weave traces agent activity using concepts such as sessions, turns, steps, tools, and sub-agents. It also provides evaluation comparisons, prompt and model exploration, production monitoring, behavior signals, alerts, and guardrail scorers. Together, these capabilities support a workflow that moves from debugging an interaction to evaluating a change and monitoring its effect in production.
W&B Weave 能做什么？
Evaluation comparisons
Uses an imperative evaluation API to compare changes to agent context, harnesses, and models, with visualizations intended to expose regressions.
Production behavior monitoring
Built-in and custom signals classify agent interactions at scale, while alerts can send selected findings to Slack notifications or webhook automations.
Prompt and model Playground
Lets teams explore prompts and models before implementation, troubleshoot production issues, and test LLMs or custom models against production traces.
Guardrails and quality scorers
Provides pre-built scorers for toxicity, bias, PII detection, hallucinations, coherence, fluency, and context relevance.
Evaluation leaderboards
Aggregates evaluation results into leaderboards that can be shared across an organization to compare performers.
使用场景
“Debug a failing agent session”
Developers can follow a multi-step or multi-agent interaction through its sessions, turns, tools, and sub-agents to investigate behavior that is difficult to interpret from raw logs.
“Validate a prompt, model, or harness change”
AI teams can run evaluations and compare alternative prompts, models, or agent harnesses before releasing an iteration, helping identify improvements and regressions.
“Investigate production issues”
Teams can use production traces in the Playground to reproduce or troubleshoot problematic outputs and test potential prompt or model changes against real interactions.
“Monitor safety and quality signals”
Product and engineering teams can apply built-in or custom signals and guardrail scorers to identify issues such as toxicity, PII, hallucinations, bias, or weak context relevance.
“Share model and evaluation results”
Organizations can collect evaluation outcomes in leaderboards so teams can compare results and communicate which models or configurations perform best for a defined use case.
常见问题
What is W&B Weave used for?
Weave is used to trace and debug AI agents and applications, evaluate prompts, models, and agent changes, and monitor behavior in production.
Can Weave handle multi-agent systems?
The product page describes sessions, turns, steps, tools, and sub-agents as first-class tracing concepts for navigating multi-turn and multi-agent execution.
Can teams evaluate changes against production behavior?
Yes. The Playground can test new LLMs and custom models against production traces, and the evaluation workflow compares changes such as prompts, models, context, and agent harnesses.
What types of safety and quality checks are available?
The page lists scorers for toxicity, bias, PII detection, hallucinations, coherence, fluency, and context relevance.
How is Weave usage billed?
The pricing page states that Weave data ingestion is billed according to usage. It defines ingested bytes as data received, processed, and stored on behalf of the customer, including trace metadata and logged LLM inputs and outputs.
快速信息
- Product category
- AI observability and evaluation
- Primary users
- Teams developing and operating AI agents and applications
- Core workflow
- Trace, evaluate, troubleshoot, and monitor agent behavior
- Monitoring model
- Sessions, turns, steps, tools, and sub-agents
- Pricing structure
- Free, Pro, and Enterprise offerings; Weave data ingestion is usage-based
- Product domain
- wandb.ai
W&B Weave 替代品
OpenController
www.lyzr.ai
OpenController is Lyzr’s control plane for discovering, evaluating, governing, and monitoring AI agents, models, tools, data, and workflows across an enterprise AI estate. It is intended for teams managing agents across clouds, frameworks, runtimes, and environments.
LangSmith
www.langchain.com
LangSmith is an observability and evaluation platform for AI agents and LLM applications. It helps development and production teams trace agent behavior, monitor quality and cost, investigate failures, and evaluate changes.
Galileo
www.galileo.ai
Galileo is an AI observability and evaluation platform for testing, debugging, and governing LLM and agent systems across development and production. It helps teams turn evaluation results into production guardrails and monitor AI behavior at scale.
TensorZero
www.tensorzero.com
TensorZero is an open-source LLMOps platform for building and operating production-grade LLM applications. Its stated scope combines an LLM gateway with observability, evaluation, optimization, and experimentation tools.
Phoenix
arize.com
Phoenix is an open-source, local-first platform for tracing, evaluating, experimenting with, and improving AI applications and agents. It helps AI engineers inspect agent behavior, assess output quality, and test changes before deployment.
inferock-bench
inferock.ai
inferock-bench is a local diagnostic proxy for tracking LLM API usage, provider-reported costs, failures, and billing-integrity signals. It helps developers inspect calls to OpenAI, Anthropic, Gemini Developer API, and pinned OpenRouter endpoints using locally stored receipts.