Searchlight is an AI-powered talent evaluation platform that utilizes predictive analytics to enhance candidate screening and assessment processes, enabling recruiters to identify the top 1% of candidates efficiently. By automating reference checks and measuring quality of hire metrics, Searchlight significantly reduces time-to-fill and improves hiring accuracy, resulting in a 40% faster recruitment process and a 20% lower cost per hire.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional candidate screening processes often rely on subjective evaluations and limited data, leading to inefficient hiring decisions and increased risk of mis-hires. Recruiters struggle to effectively assess soft skills, predict candidate performance, and ensure a fair and unbiased evaluation process. This results in longer time-to-fill, higher costs per hire, and potential negative impacts on overall quality of hire.
Solution
Searchlight offers an AI-powered talent evaluation platform that leverages predictive analytics to streamline candidate screening and improve hiring accuracy. The platform uses AI to screen candidates based on relevant work experiences, hard skills, and soft skills. Searchlight automates reference checks to gather predictive data on a candidate's skills, culture fit, and potential performance. The platform also measures quality of hire metrics to provide visibility on hiring quality and employee outcomes. By integrating these features, Searchlight helps recruiters make more objective, data-driven decisions, reduce time-to-fill, and lower costs per hire.
Target Audience
Searchlight primarily targets recruiting teams and HR leaders committed to improving hiring effectiveness and efficiency, particularly those in medium to large organizations.
Features
- AI-powered applicant screening that filters candidates based on work experience, hard skills, and soft skills
- Automated reference checks that gather predictive data on skills, culture fit, and potential performance
- Customizable assessments validated by I/O science to evaluate candidates for skills and culture fit
- Quality of Hire (QoH) metrics to track hiring quality and employee outcomes
- Bias-free AI algorithms to ensure fair and objective candidate evaluations
- Integration with existing applicant tracking systems (ATS)
- Reporting and analytics dashboards to visualize hiring data and trends