AI Recruiting Data Quality Agent

How Cassidy automates using AI

Step 1: Trigger on data sync events

The Workflow activates when new applications, stage changes, or candidate updates arrive via ATS webhooks, HRIS batch syncs, or job board imports—capturing source attribution and UTM parameters at intake.

Step 2: Parse and normalize incoming records

Cassidy extracts structured data from resumes and profiles, then maps fields to your canonical schema—standardizing job titles, skills, locations, and disposition codes against your approved taxonomies.

Step 3: Deduplicate and create golden records

The agent applies fuzzy matching on names, emails, and employment history to identify duplicate candidates and applications, then merges them according to your survivorship rules while maintaining full audit trails.

Step 4: Validate compliance and data quality

Cassidy runs business rule checks for EEO field completeness, valid stage sequences, and correct job group mappings—flagging exceptions to a review queue with specific remediation guidance.

Step 5: Enrich and publish clean data

The Workflow appends missing company metadata, infers seniority levels, and pushes conformed facts and dimensions to your warehouse—ready for BI tools and OFCCP reporting with complete lineage documentation.