Generate, evaluate, iterate: synthetic data to supercharge AI judges

Kari Jaaskelainen

07 Nov 2025 — 1 min read

Teach your AI judge—faster—with synthetic test cases

Evaluating AI with "LLM-as-a-judge" works—until you run out of good examples. This study introduces a tool that generates rich, customizable synthetic test cases to refine your evaluation criteria, all within a human-in-the-loop workflow.

Configure domains, personas, lengths, desired outcomes—even borderline cases.
AI-assisted inline editing to tweak existing tests.
Full transparency: see the prompts and explanations used to generate each case.

In a user study (N=24), 83% preferred this tool over manual test creation, citing speed and diversity without extra workload. Crucially, synthetic data was as effective as hand-crafted data for improving evaluation rubrics and aligning with human preferences.

Generate. Evaluate. Iterate. Scale your AI evaluations without sacrificing quality.

Paper: http://arxiv.org/abs/2511.04478v1

Paper: http://arxiv.org/abs/2511.04478v1

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AI LLM SyntheticData Evaluation HumanInTheLoop HCI ML Research AIEvaluation

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