DivERS utilizes an AI-powered platform that automates candidate screening and anonymizes data to eliminate biases related to gender and nationality during the recruitment process. This technology enables employers to focus solely on applicant qualifications, resulting in a faster and more equitable hiring experience.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional recruitment processes often suffer from unconscious biases related to gender, nationality, or other demographic factors, leading to a non-optimal selection of candidates. Manual screening methods are time-consuming and prone to subjective evaluations, hindering the ability to efficiently identify the most qualified individuals.
Solution
DivERS offers an AI-powered platform, named Mithra, that automates candidate screening and anonymizes applicant data to mitigate biases during the recruitment process. The platform uses a combination of proprietary and foundational large language models (LLMs), leveraging technologies like LangGraph and LangChain for transparent and precise candidate assessments. By prioritizing candidate self-assessment through job-specific questions, DivERS aims to create a fair and thoughtful connection between candidates and companies, focusing on skills-based hiring and real potential. The system provides a streamlined, unbiased, and transparent solution for comprehensive candidate analysis.
Target Audience
DivERS primarily targets HR departments, recruiters, and hiring managers within organizations seeking to streamline their recruitment processes, reduce bias, and improve the quality of their hires, with a focus on volume recruitment.
Features
- AI-driven candidate screening using proprietary and foundational LLM models
- Anonymization of applicant data to eliminate unconscious biases
- Job-specific self-assessment questionnaires for fair candidate evaluation
- Automated shortlisting based on skills and qualifications
- Unbiased LinkedIn insights for clearer candidate selection
- Transparent communication features to enhance candidate experience