What could better hiring return for your organization?
Estimate the annual value of structured, science-based hiring — grounded in published industry benchmarks. Adjust every assumption to match your reality.
Estimate the annual value of structured, science-based hiring — grounded in published industry benchmarks. Adjust every assumption to match your reality.
Quick inputs — results update instantly.
Every hiring decision on the platform is made by a human. Assessments are scored with IO-psychologist-defined formulas and interviews are evaluated by trained humans using structured methods — AI supports, it never decides. That human-verified architecture is built for responsible AI in hiring:
Candidate identity verification (selfie + government-issued photo ID) can be required per job before interviews. Candidate fraud is escalating: Gartner projects 1 in 4 candidate profiles will be fake by 2028, 41% of security leaders report having onboarded a fraudulent candidate, and a single detection incident averages ~$28,000. Like compliance, this value is real but organization-specific — so we don’t put a number on it.
See the platform in action with a personalized product demo.
Recruiter time returned = hires × recruiter hours saved per hire × recruiter loaded hourly cost. Industry time studies estimate roughly 23 hours of screening, scheduling, and correspondence per hire; the default assumes less than half of that is recovered.
Hiring-manager time returned = hires × hiring-manager hours saved per hire × loaded hourly cost. Pre-screening and structured assessments mean managers interview a smaller, qualified slate.
Faster time-to-fill = hires × days reduced × daily cost of vacancy. Daily cost of vacancy uses the standard formula (annual salary ÷ 260 working days) with a conservative impact factor of 1.0. US average time-to-fill is 42–44 days (SHRM 2025 Benchmarking).
Better quality of hire = hires × industry first-year turnover rate × early-turnover reduction × replacement cost. Replacement cost uses the U.S. Department of Labor's conservative estimate of 30% of first-year earnings per mis-hire. Industry turnover benchmarks from Mercer and industry surveys (2025). Published research on validated pre-hire assessments reports early-turnover reductions of ~22%; the default here is set lower.
Agency fees avoided = hires × share filled via agencies × agency fee × average salary. Contingency agency fees typically run 15–25% of first-year salary (20% is the common benchmark).
Smarter advertising spend = annual job advertising spend × savings rate. Our programmatic advertising partner’s platform data (2025) shows a 23% year-on-year reduction in cost-per-application — 17% more sponsored applications delivered on a 10% smaller budget. Roughly 40% of traditional job-ad spend is wasted on channels that fail to produce quality applicants (Aptitude Research). The default savings rate (20%) is deliberately set below the partner-measured 23%.
Fewer declined offers = hires × offer-decline rate × decline reduction × restart cost. Restart cost uses the SHRM 2025 average cost per hire ($5,475). Market-aligned, transparent compensation improves offer acceptance by 15–25% (Gartner / Indeed Hiring Lab); the default reduction is set lower.
Compliance value and identity assurance are intentionally not assigned a dollar figure. Avoided regulatory and fraud exposure is real but organization-specific.
This calculator provides directional estimates based on published third-party benchmarks and adjustable assumptions. It is not a guarantee of results, savings, or performance. Benchmark sources: SHRM 2025 Benchmarking Report (average cost per hire $5,475; time-to-fill 42–44 days); U.S. Department of Labor (bad-hire cost ≥ 30% of first-year earnings); Mercer 2025 US Turnover Surveys; standard industry cost-of-vacancy methodology; Aptitude Research (job-ad spend waste); programmatic advertising partner platform data, 2025 (cost-per-application); Gartner (candidate fraud projections, offer acceptance). In hourly mode, pay is annualized at 2,080 working hours per year. Model v4 — July 2026.