Predictive hiring platform with assessments, video interviews, and automated candidate workflows
Harver operates a hiring platform built on SQL Server, MongoDB, and AWS, anchored by predictive models (Random Forest, XGBoost) trained on 35+ years of industrial-organizational psychology research. Active projects in identity automation, pricing tools, and ROI analysis—paired with pain points around time-sensitive production issues and CRM hygiene—reveal a company balancing platform maturity with operational scaling. Senior-heavy hiring across engineering and data signals investment in model rigor and infrastructure reliability.
Harver is a talent acquisition platform that combines predictive assessments, video interviews, scheduling, and reference checking to streamline hiring workflows. The product is rooted in industrial-organizational psychology and cognitive science, applied to reduce bias and improve candidate experience at scale. The company has processed over 100 million candidates across more than 1,300 customers worldwide. Harver operates globally from its New York headquarters, with engineering and go-to-market teams distributed across the United States, Netherlands, and United Kingdom. Current priorities include EMEA market expansion, North America scaling, and strengthening internal systems for candidate data standardization and sales enablement.
Harver builds on SQL Server and MongoDB for persistence, AWS for infrastructure, with Python for model work (Random Forest, XGBoost). Frontend uses HTML, CSS, and JavaScript. Identity and access managed via SAML and Okta; analytics via Looker.
Harver has processed over 100 million candidates across more than 1,300 customers globally since its founding in 2015, serving talent teams across multiple industries and geographies.
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