Recrewty provides an AI-powered platform that assesses candidates' soft skills, attitude, and cultural fit to improve hiring decisions. Its proprietary psychological assessments and machine learning algorithms generate objective hiring signals, enabling organizations to create unbiased, ranked candidate shortlists and reduce employee turnover.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional recruitment processes often prioritize technical qualifications and past experience over essential soft skills, attitude, and cultural alignment. This reliance on CV screening can lead to suboptimal hiring decisions, resulting in increased employee turnover and prolonged recruitment cycles.
Solution
Recrewty offers an AI-powered platform designed to assess candidates' soft skills, attitude, and cultural fit, providing a more holistic view beyond traditional CV analysis. The system utilizes proprietary psychological assessments and machine learning algorithms to generate objective hiring signals. This data-driven approach enables organizations to create unbiased, ranked candidate shortlists, thereby accelerating the hiring process, improving employee retention rates, and reducing the administrative burden on HR departments.
Target Audience
Recrewty serves HR departments and hiring managers within organizations seeking to enhance the quality and efficiency of their recruitment efforts by focusing on candidate potential and fit.
Features
- AI-driven assessment engine that evaluates candidates on soft skills, attitude, and cultural alignment.
- Proprietary psychological assessment modules designed to elicit behavioral and attitudinal data.
- Machine learning models that analyze assessment results to generate quantifiable hiring signals.
- Automated candidate ranking system to produce unbiased, data-backed shortlists.
- Workflow integration for seamless candidate assessment and evaluation within existing HR processes.
- Analytics dashboard providing insights into candidate profiles and hiring decision rationale.
- Bias mitigation features embedded within the assessment and scoring methodologies.