An LLM Evaluation Agent that you can describe to it what you want to evaluate in natural language — the expert AI agent handles dataset generation, judge configuration, execution, and analysis end-to-end, and hands you back a PDF report.

Features
Expert agent interface — The agent knows evaluation best practices, recommends criteria and validates configurations before execution. No config files or CLI expertise needed.
Jury system — Multiple judges from different model families (e.g. Claude Sonnet, Nova Pro, Nemotron) each evaluate distinct aspects of every response — correctness, reasoning, completeness. Combining diverse judge families reduces self-preference bias, and aggregating weak signals from diverse judges and criteria produces stronger results than any single judge (Verma et al., 2025, Frick et al., 2025).
Adaptable binary scoring — Binary pass/fail per criteria rather than subjective numeric scales, shown to produce more reliable results across judges (Chiang et al., 2025). Criteria are tailored by the agent to what you're evaluating.
Document-grounded synthetic data — Upload PDFs, knowledge bases, or product docs and generate QA pairs grounded in your actual content, reflecting real customer scenarios.
Agentic eval support — Evaluate any agent calling Bedrock (Strands, LangChain, custom boto3) with zero code modification via OpenTelemetry instrumentation.