AI Recruiting Analytics Report Agent

How Cassidy automates recruiting analytics using AI

Step 1: Connect recruiting data sources

Cassidy syncs with your ATS (Greenhouse, Lever, Ashby), HRIS, scheduling tools, and sourcing platforms via native integrations or API, continuously ingesting candidate events, stage moves, interviews, offers, and headcount plans into the Knowledge Base.

Step 2: Standardize metrics and stage taxonomy

The Workflow normalizes job-specific stages into consistent stage groups, deduplicates candidates, and applies your defined metric logic—pass-through rates, time-in-stage, SLA thresholds—so every report uses the same trusted definitions.

Step 3: Generate role-based dashboards

Cassidy compiles operational views for recruiters (active reqs, aging candidates, scheduling backlog), analytical dashboards for TA analysts (funnel conversion, source quality, DEI breakdowns), and executive summaries (hires vs plan, cost per hire, forecast accuracy).

Step 4: Distribute scheduled KPI digests

At your chosen cadence, Cassidy packages key metrics—new applications, PTR shifts, SLA attainment, offer outcomes—into audience-specific digests with auto-generated narrative insights, then delivers them to Slack, Teams, or email.

Step 5: Trigger real-time alerts

When thresholds are breached—candidate stuck in HM review, PTR drop below baseline, interviewer capacity over limit, adverse-impact ratio flagged—Cassidy routes alerts to the responsible owner with context and recommended next actions.

Step 6: Surface forecasts and planning insights

Using historical PTRs and time-in-stage data, Cassidy projects hires by week, highlights gaps to headcount plan, and calculates required top-of-funnel volume—giving TA leaders the runway visibility to intervene early.