Harver is a hiring and talent selection platform built on industrial-organizational psychology and predictive modeling. The tech stack—Python, Random Forest, XGBoost, SQL Server, MongoDB—reflects a data-science foundation for assessments and candidate ranking. Current project work spans AI adoption across go-to-market operations, pipeline forecasting, and automation of operational workflows, indicating the company is shifting from pure hiring tools toward embedded revenue intelligence and operational efficiency.
Harver provides a suite of hiring solutions including skills assessments, video interviews, scheduling, and reference checking, designed to reduce bias and automate candidate selection. The company operates across North America and Europe, with a customer base spanning over 1,300 organizations. Founded in 2015 and headquartered in Atlanta, Harver is a 51–200 person, privately held company. The current hiring emphasis on sales roles and senior talent, combined with projects around international expansion and private equity reporting compliance, suggests scaling go-to-market functions and operational infrastructure to serve larger deal sizes.
Harver's core tech includes Python and SQL Server for backend systems, MongoDB for data storage, and machine-learning libraries (Random Forest, XGBoost) for predictive models. The GTM and finance operations run on Salesforce, Sage Intacct, and Tipalti; engineering uses TypeScript, Jira, and AWS infrastructure.
Current projects include AI adoption across the go-to-market organization, AI-driven pipeline forecasting, automation of accounting and operational workflows, M&A due diligence capabilities, international expansion, and retention management. The company is also addressing private equity reporting compliance and audit coordination.
Harver's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.