ERIN is an AI-powered employee referral platform that helps companies hire faster, reduce recruiting costs, and turn their workforce into a high-performing hiring channel.
Built for modern talent acquisition teams, ERIN automates the entire referral lifecycle, from employee engagement and candidate submission to eligibility enforcement, payouts, and ROI reporting. No spreadsheets. No manual tracking. No administrative drag.
Companies using ERIN consistently see more referral hires, faster time to fill, and higher retention, all while creating a better experience for employees and recruiters alike.
AI-Powered Referral Performance
ERIN uses AI to identify the right employees to engage, recommend the right jobs to share, and automate personalized outreach through email and text. This drives higher participation, better candidate quality, and stronger conversion rates without increasing recruiter workload.
Fully Automated, Enterprise-Ready
ERIN eliminates manual work by automatically handling duplicate detection, eligibility rules, compliance, approvals, and bonus payouts. Enterprise teams get the scale, security, and governance they need without sacrificing speed or flexibility.
Seamless Integration with Your Hiring Stack
ERIN integrates with leading ATS, HRIS, and payroll systems so referral activity flows directly into your existing processes with no disruption and no custom development.
Employee-First Experience
Employees can submit referrals in seconds from any device and track progress and rewards in real time. The easier it is to refer, the more your program performs.
Real Analytics, Real ROI
Built-in reporting gives talent teams clear visibility into referral volume, hire rates, bonus spend, and overall ROI so leaders can prove impact and optimize performance.
Start Fast with a Free Trial
ERIN offers a free trial so you can launch quickly, activate your workforce, and see real results from AI-powered referrals without long implementation cycles.
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German, English, French, Italian, Portuguese, Russian, Spanish
Overview by
Mike Stafiej