Agents
Observability tools for building autonomous AI systems that perform multi-step tasks
W&B Weave provides the tools you need to evaluate, monitor, and iterate on agentic AI systems during both development and production. With traces, scorers, guardrails, and a registry, you can confidently build and manage safe, high-quality agents and agentic workflows.
Evaluations
Agentic systems are complex and involve many different components, making eval metrics more difficult to build and track. Weave evaluates agents quickly using pre-built, third-party, or homegrown scorers, increasing iteration velocity.
Debugger
Agents organize their tasks into sequences of steps, each performing a variety of actions such as calling tools, reflecting on outputs, and retrieving relevant data. Debugging and iterating on these complex rollouts can be challenging with traditional call-stack views. Weave clearly visualizes complex agent rollouts to accelerate the iteration process.
Guardrails
Since LLMs are non-deterministic, you need the ability to modify agent inputs and outputs when harmful, inappropriate, or off-brand content is detected. Weave enables real-time adjustments to agent behavior to mitigate the impact of hallucinations and prompt attacks.
Integrations
New agent frameworks are coming to market rapidly, making it difficult to keep up. Through integrations with popular frameworks such as CrewAI and OpenAI Agents SKD, Weave helps you stay future-proof, ensuring your agents won’t become obsolete as new frameworks emerge.
Governance
For compliance and audits, developers need the ability to rebuild specific agents versions and configurations and reproduce events arising in production. Weights & Biases acts as a system of record and allows AI developers to reproduce any task in the agent lifecycle by providing code, dataset, and metadata versioning and lineage tracking.
The Weights & Biases end-to-end AI developer platform
Weave
Models
The Weights & Biases platform helps you streamline your workflow from end to end
Models
Experiments
Track and visualize your ML experiments
Sweeps
Optimize your hyperparameters
Registry
Publish and share your ML models and datasets
Automations
Trigger workflows automatically
Weave
Traces
Explore and
debug LLMs
Evaluations
Rigorous evaluations of GenAI applications