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Dictionary

AI Evals

Reproducible test suites that measure LLM output quality across model, prompt and code changes.

1 min readupdated 2026-06-21

/ quick answer

Evals are the unit tests of AI systems. You define a labeled dataset and scoring functions (exact match, rubric grading, LLM-as-judge) and run them on every change — so you catch regressions when swapping models, tweaking prompts or upgrading a tool.

Reproducible test suites that measure LLM output quality across model, prompt and code changes. Evals are the unit tests of AI systems. You define a labeled dataset and scoring functions (exact match, rubric grading, LLM-as-judge) and run them on every change — so you catch regressions when swapping models, tweaking prompts or upgrading a tool. In practice: Before promoting a new system prompt, a team runs 200 saved customer questions through both the old and new prompt and compares helpfulness, accuracy and refusal rates side by side. This dictionary node is part of the Onexial knowledge graph and links to related concepts, workflows and tools below.
Definition
Evals are the unit tests of AI systems. You define a labeled dataset and scoring functions (exact match, rubric grading, LLM-as-judge) and run them on every change — so you catch regressions when swapping models, tweaking prompts or upgrading a tool.
Example
Before promoting a new system prompt, a team runs 200 saved customer questions through both the old and new prompt and compares helpfulness, accuracy and refusal rates side by side.
Related Workflows
Related Tool Stacks
/ frequently asked

What is AI Evals?

Evals are the unit tests of AI systems. You define a labeled dataset and scoring functions (exact match, rubric grading, LLM-as-judge) and run them on every change — so you catch regressions when swapping models, tweaking prompts or upgrading a tool.

What is an example of AI Evals?

Before promoting a new system prompt, a team runs 200 saved customer questions through both the old and new prompt and compares helpfulness, accuracy and refusal rates side by side.

Why does AI Evals matter for AI and automation?

Reproducible test suites that measure LLM output quality across model, prompt and code changes. It connects to the workflows, prompts and tool stacks linked on this page, so you can move from definition to execution without leaving Onexial.

/ topics#ai#ops#testing
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