Show HN: AI Screened Applicants

We built a Resume parser trained on an AI model using resume and personality data from top performing knowledge workers in a given category, we then use that to identify common characteristics of top performing workers and stack them against new candidate clusters for initial screening. Once candidates are screened, we sync them to a video call using image recognition software and voice emotion analysis, where we benchmark personality traits using an AI model to identify common characteristics of top performing workers and stack them against qualified candidates, a collective profile is then generated for each analysis generating visual analytics reports and ranking them into quartiles for various categories. The outcome results in superior candidate selection, reduction of cognitive bias and other human based variability errors while reducing HR hours.