Objective, data-backed guidance for every salary decision.

Compensation decisions can easily become subjective, political, or inconsistent across teams. Evenpay solves this by calculating an ideal salary for every employee based on how your organization actually values experience, competence, performance, responsibilities, education, and other objective factors. Using the same ML-algorithms that powers your pay-gap reporting, the system identifies exactly where each employee should sit relative to peers.

This gives HR and managers a crystal-clear view of under- or over-compensation. Instead of vague feelings or historical habits, they see a mathematically grounded benchmark that reflects the company’s own pay structure — not market estimates or external opinions.

Salary recommendations become the natural starting point for any compensation review. Managers can compare their team’s pay positioning against the organization-wide model, understand the rationale, and decide how to close gaps or justify differences. It reduces friction, eliminates bias, and ensures consistent decisions across departments.

Because recommendations are generated from your internal data — not generic formulas — they adapt as your workforce evolves. Promotions, new skill levels, changing role demands, and updated performance outcomes all feed into the model, keeping recommendations accurate and aligned with real contribution.

Over time, leaders gain a clearer understanding of how fairly their organization compensates people, where structural issues may exist, and which roles or units require attention. It is one of the simplest and most reliable ways to bring fairness, transparency, and discipline into compensation.