AI Recruiting KPI Report Agent

How Cassidy automates recruiting analytics using AI

Step 1: Trigger on weekly schedule or data refresh

The Workflow activates automatically on a set cadence—weekly, daily, or when new data lands from your ATS, HRIS, or sourcing tools via API or webhook.

Step 2: Extract and normalize recruiting data

Cassidy pulls requisitions, candidates, stage transitions, and offers from connected systems, then standardizes entities to a common schema—deduplicating candidates and mapping business units, job families, and recruiters.

Step 3: Calculate funnel and velocity KPIs

The Workflow computes passthrough rates by stage, time-to-fill, time-to-hire, offer acceptance rates, source ROI, and recruiter productivity metrics using certified definitions from your Knowledge Base.

Step 4: Analyze DEI funnel and flag exceptions

Cassidy calculates representation and selection rates at each decision gate, applies the 80% adverse impact rule, and flags non-compliant diverse slates or skewed panel diversity—with privacy thresholds enforced.

Step 5: Detect alerts and pipeline risks

The agent identifies SLA breaches, bottlenecks, thin top-of-funnel, aging reqs, and data quality issues, then prioritizes them by business impact.

Step 6: Generate and distribute HRBP dashboards

Cassidy compiles role-based scorecards with hires vs. plan, velocity trends, DEI flags, and recommended actions—then delivers weekly digests via Slack, Teams, or email with deep links to interactive views.