AI Compensation Equity Reporting Agent

How Cassidy automates using AI

Step 1: Trigger on reporting cycle or data refresh

The Workflow activates on a scheduled cadence—quarterly, annually, or when HRIS/payroll data updates—pulling structured employee, compensation, and job architecture data from connected systems like Workday, SAP SuccessFactors, or ADP.

Step 2: Normalize and map job architecture

Cassidy cleanses incoming data, normalizes job titles, applies currency and FTE rules, and maps roles to job families, levels, and equal-value groupings using your organization's evaluation framework stored in the Knowledge Base.

Step 3: Run adjusted and unadjusted gap analytics

The agent executes multivariate regression controlling for legitimate factors—job level, location, tenure, performance, contract type—and calculates mean/median gaps, quartile distributions, and variable pay breakdowns aligned to EU metrics.

Step 4: Generate explainability outputs and flag outliers

Cassidy surfaces driver decomposition, coefficient effects, and individual-level reference comparisons, flagging employees paid materially above or below predicted pay and identifying categories that exceed the 5% unexplained gap threshold.

Step 5: Produce jurisdiction-specific compliance reports

The Workflow assembles submission-ready files with localized templates, management attestation language, and public disclosure narratives—automatically routing drafts to legal, HR, and executive stakeholders for Human-in-the-Loop review.

Step 6: Model remediation scenarios and route for approval

Cassidy simulates optimized pay adjustments to close unexplained gaps within budget and band constraints, then routes recommendations through your approval workflow with cost projections, impact estimates, and implementation phasing for the next comp cycle.