Evals
AI performance measured on real comp workflows
Compa Evals are your system for measuring how reliably AI agents perform compensation work so you deploy AI with confidence, clarity, and control.
Trusted by compensation leaders managing billion-dollar portfolios

In compensation,
“mostly right” is still wrong
AI demos look impressive, but comp teams are left guessing about reliability, hidden risks, and the defensibility of outputs to business partners.
Compa Evals separate observability from evaluation
Observability tells you what the AI did. Evaluation tells you if it did the job well.
Compa Evals keeps those signals separate, so output quality isn’t diluted by speed, volume, or cost.
Prompts come directly from enterprise comp workflows like market analysis, employee benchmarking, segmentation, and edge cases.

Human compensation experts evaluate AI outputs against four categories: accuracy, completeness, assumptions, and usability.
See agent improvements, limitations, and how changes impact compensation proficiency.
Evaluations happen in a controlled environment so results stay comparable across releases. You control for context, tools, and configuration.
Outputs are consolidated into reliability scorecards for each compensation workflow and tracked monthly.
Every compensation workflow comes with a reliability score, tracked over time and tied directly to comp work.
Scores are published, updated, and tested under constraints. If a score is ever 100%, it would mean we aren’t testing hard enough.
