To modernize HireRight’s employment verification process and address the rising operational inefficiencies, Gantec applied its proven 4-step AI advisory methodology—Assessment, Analyze, Identify Use Cases, and Recommendations. This structured, outcome-driven approach ensured each solution was directly aligned with HireRight’s business goals and operational realities.

Methodology:

Gantec initiated a discovery and assessment phase to gain a deep understanding of HireRight’s operational metrics, particularly around Criminal and Verification workflows. Using a data-first lens, our team analyzed where AI and automation could deliver measurable impact and improve speed, cost-efficiency, and reliability. Collaborative workshops helped identify key areas for transformation.

Integration Process:

A unified data platform was designed to consolidate verification data, support machine learning workflows, and enable real-time decision-making. The integration allowed historical verification data to be stored, queried, and reused—eliminating unnecessary repeat verifications. Data pipelines were built to organize and feed ML models that intelligently match employer names, route requests to optimal vendors, and trigger instant verification where possible.

Customizations & Design Considerations:

Historical Data Reuse: Enabled 6–8% re-verification avoidance by leveraging past employment/education checks.
Vendor Optimization: ML-driven selection logic improved fulfillment reliability and controlled costs.
Employer Name Matching: Automated fuzzy matching reduced manual effort and increased accuracy.
Instant Verification Enablement: Integration-ready framework for current and recent employment checks via automated sources.
Audit & Transparency Controls: Designed to improve oversight and reduce vendor dependency through measurable performance tracking.