W&B Weave

Overview

W&B Weave is a production observability and improvement platform for AI agents, with tracing, monitoring and evaluation in one toolkit. It is best suited to teams building language-model applications that need to inspect agent behavior and assess changes before deployment. Its breadth is useful, but the monthly ingestion caps make usage costs worth checking before choosing a paid plan.

Founded in 2017 in San Francisco, Weights & Biases was acquired by CoreWeave in May 2025. Weave tracks agent activity alongside model costs, prompts and retrieval, making it relevant to AI Agent Observability Tools, AI LLM Observability Tools, LLM Observability Tools, Model Monitoring Software and AI Agent Evaluation Tools.

Key features

Agent tracing and monitoring

Weave organizes traces into sessions and turns, treating steps, tools and sub-agents as distinct concepts. That structure is useful when a team needs to follow a multi-step interaction rather than view model calls in isolation. Built-in and custom signals capture and classify interactions, while Slack notifications and webhook automations can route alerts to existing workflows.

Cost and token tracking, prompt management, LLM tracing and retrieval tracing broaden the view beyond agent steps. Python and TypeScript libraries, an OTLP endpoint for OpenTelemetry traces, and integrations with LangChain, LlamaIndex, OpenAI, Meta, Amazon Bedrock and Anthropic give teams several ways to connect their stack.

Evaluations, experimentation and guardrails

The evaluation framework offers comparisons and visualizations to help teams spot regressions before deployment. In the Playground, users can compare models and prompting approaches against production traces, tying experimentation to observed application behavior.

Pre-built safety scorers cover toxicity, bias, personally identifiable information and hallucinations; quality scorers assess coherence, fluency and context relevance. These provide useful starting points for assessment, while custom signals allow teams to reflect their own monitoring needs.

Security

W&B states that its platform is certified to ISO/IEC 27001:2022, ISO/IEC 27017:2015 and ISO/IEC 27018:2019, and compliant with SOC 2 Type 2 and HIPAA standards. Data is encrypted in transit with TLS 1.2+ and at rest with AES 256. Enterprise pricing includes options such as single sign-on, audit logs, secure private connectivity and customer-managed encryption keys, which matter to organizations with stricter access or data controls.

Pricing

Weave uses a freemium model, with a 30-day trial and paid plans from $60/mo.

Free covers core evaluation and tracing, but its 1 GB monthly ingestion allowance and 5 GB storage cap may constrain applications with sustained trace volume. Pro adds just 0.5 GB/mo over Free, so the $0.10/MB charge for additional ingestion is a key cost consideration; its intended audience is organizations with fewer than 50 employees. Pro also includes priority email and chat support. Enterprise suits organizations needing configurable usage or stronger administrative and security controls, with an enterprise support package, but requires custom pricing and annual upfront invoicing.

Platforms

Weave supports API, Linux, macOS, self-hosted, web and Windows environments. Deployment options include both hosted and self-hosted approaches.

Who it's for

Weave is a strong fit for teams operating production AI agents that need to connect traces, evaluations, cost tracking and alerts in a shared workflow. The session-and-turn model and first-class treatment of tools and sub-agents are particularly relevant to applications with multi-step agent behavior. Teams with light usage can start on Free; teams expecting heavier ingestion should estimate volume against Pro’s modest allowance before committing. Organizations requiring enterprise access controls or security options can consider custom Enterprise pricing. It is less compelling for users who only need a standalone evaluator or who want predictable higher-volume ingestion at the entry paid tier.

Pros and cons

• Pros: Agent traces distinguish sessions, turns, steps, tools and sub-agents, giving teams a structured way to inspect complex interactions.
• Pros: Evaluations, production-trace comparisons, built-in scorers and alert routing connect assessment with ongoing monitoring.
• Pros: Python and TypeScript SDKs, OpenTelemetry support and integrations across frameworks and model providers accommodate varied stacks.
• Cons: Free is capped at 1 GB/mo ingestion and 5 GB/mo storage, which may be restrictive for busy applications.
• Cons: Pro starts at $60/month for 1.5 GB/mo, and additional ingestion costs $0.10/MB, so usage can materially affect the bill.
• Cons: Enterprise pricing is custom and invoiced annually upfront, a less flexible commitment for teams that need enterprise controls.

Alternatives

Evidently AI is a free, open-source Apache 2.0 framework for teams prioritizing an open-source option. OpenLIT is a free alternative whose OSS plan offers unlimited self-hosted usage, users, projects and environments, with community support through GitHub. Promptfoo may suit teams centered on evaluation and red-teaming: its free Community plan includes 10k red-team probes/month, all LLM evaluation features and local or self-hosted runs.

Opik is worth considering if running open-source observability and evaluation features locally is a priority. Langfuse offers a Hobby plan with 50k units/month, 30 days of data access and two users for teams comparing a defined free allowance. Arize AX provides a free SaaS tier with 25k trace spans/month, 1 GB ingestion/month, 15-day retention, unlimited users and evaluations, and a 10-issue Signal limit.

Confident AI is another freemium option. Galileo is another freemium option.

Verdict

Choose W&B Weave if your team needs production agent tracing, evaluation, monitoring and experimentation together, especially when tools and sub-agents make behavior difficult to follow. Its integrations and range of signals support a broad workflow, but the limited Pro ingestion allowance and per-MB overage mean it is not the safest choice for teams with high or unpredictable trace volume. Check expected usage first, and look elsewhere if open-source deployment or a generous fixed ingestion allowance is the priority.