Trusted AI agents and applications require rigorous evaluations
Deploy your AI systems with confidence
Evaluations measure the performance of AI agents and applications across multiple dimensions, including quality, latency, cost, and safety. Using a combination of benchmark tests, real-world scenarios, and comparative analysis, evaluations assess an AI application’s predictability and proficiency in problem-solving and task execution. The results reveal how well it performs and where it needs improvement.
Benefits of using evaluations
Go beyond “vibe checks” and gain necessary visibility and insight into your AI agent or application behavior.
Protect your brand reputation by catching and correcting bias, errors, or inconsistencies before they reach your customers.
Analyze and optimize your AI agents and applications to ensure enterprise-grade reliability and scalability.
How to evaluate your AI applications with Weave
Scorers
Weave Scorers evaluate AI inputs and outputs and return evaluation metrics.
Datasets
Weave Datasets help you to organize, collect, track, and version examples for agentic workflow evaluation for easy comparison.
Comparisons
Weave Comparisons allow you to visually compare and diff code, traces, prompts, models, and model configurations.
Trusted by the leading teams across industries—from financial institutions to eCommerce giants
Socure, a graph-defined identity verification platform, uses Weights & Biases to streamline its machine learning initiatives, keeping everyone’s wallets a little more secure.
Qualtrics, a leading experience management company, uses machine learning and Weights & Biases to improve sentiment detection models that identify gaps in their customers’ business and areas for growth.
Invitae, one of the fastest-growing genetic testing companies in the world, use Weights & Biases for medical record comprehension leading to a better understanding of disease trajectories and predictive risk.
See Weights & Biases in action
Webinar
Evaluating LLM-Powered Applications
Tutorial
Build an evaluation pipeline
Course
LLM apps: Evaluation
Blog
Building better AI applications: Why evaluations matter
Demo
How to optimize AI performance with W&B Weave
The Weights & Biases end-to-end AI developer platform
Weave
Traces
Debug agents and AI applications
Evaluations
Rigorous evaluations of agentic AI systems
Playground
Explore prompts
and models
Agents
Observability tools for agentic systems
Guardrails
Block prompt attacks and harmful outputs
Monitors
Continuously improve in prod
Models
Experiments
Track and visualize your ML experiments
Sweeps
Optimize your hyperparameters
Tables
Visualize and explore your ML data
Core
Inference
Explore hosted, open-source LLMs
Registry
Publish and share your AI models and datasets
Artifacts
Version and manage your AI pipelines
Reports
Document and share your AI insights
SDK
Log AI experiments and artifacts at scale
Automations
Trigger workflows automatically
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
Core
Artifacts
Version and manage your ML pipelines
Tables
Visualize and explore your ML data
Reports
Document and share your ML insights
SDK
Log ML experiments and artifacts at scale