Evaluation / Evals
TL;DR
Systematically measuring and assessing AI quality.
What does this mean?
Evals are tests and metrics used to measure the quality of AI outputs. They help identify whether a system is working reliably and where its weaknesses lie.
How it works
You define test cases with expected outcomes and run the AI against them. Automated and manual scoring shows how correct and helpful the responses are.
Example
Define 100 typical customer queries as a test set. The AI agent answers them, and the results are evaluated for accuracy, tone, and completeness.
Why it matters
Without evals, you’re flying blind. Systematic evaluation is the foundation for continuous improvement and trust in AI systems.
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