Matan Roginsky
Co-Founder & CEO
Novia101
Novia utilizes machine learning algorithms and large language models to perform context-aware analysis of candidates, ensuring precise alignment with company culture and job requirements. This technology addresses the challenges of false positive hires, biased selection, and overlooked talent by enabling fast, unbiased screening at scale.
- Artificial Intelligence
- Enterprise Software
- HR Technology
- Software Only
Updated 6 months ago
Funding
Funding rounds are not available yet.
Founders
Product
Problem
Traditional hiring processes often struggle with accurately assessing a candidate's fit beyond surface-level qualifications, leading to mis-hires, biased selection, and overlooking potentially strong candidates who may not perfectly match keyword-based job descriptions. This results in increased turnover, decreased productivity, and a failure to build diverse and inclusive teams.
Solution
Novia leverages AI and machine learning to provide context-aware candidate analysis, ensuring a more precise alignment with company culture, team dynamics, and specific job requirements. The platform analyzes data from multiple sources, including resumes, online profiles, and other relevant information, to decompose skills into signals and reconstruct them for effective empirical matching. By incorporating knowledge from occupational psychology experts, Novia delivers consistent and fair screening results at scale, helping companies make accurate, unbiased hiring decisions and identify hidden talent. The system evaluates candidates against company culture and dynamically adapts, ensuring a tailored fit.
Target Audience
Novia's primary customers are HR departments, hiring managers, and recruitment teams seeking to improve the quality of their hires, reduce time-to-hire, and ensure diverse and unbiased hiring practices.
Features
- AI & ML powered contextual analysis based on knowledge from occupational psychology experts
- Multi-channel validation that decomposes skills into signals for effective empirical matching
- Seamless ATS integrations for importing candidates in seconds
- Social intelligence analysis of data from multiple sources across the web
- Role context-aware analysis that evaluates candidates against company culture and dynamically adapts
- ATI Technology: ML algorithms and LLMs extract thousands of signals from company context and candidate information