Route candidates by resume fit score

HR and recruiting teams manually review each incoming resume to extract candidate information, compare qualifications against job requirements, and determine which applicants should advance to the next stage. This creates significant bottlenecks in high volume hiring, delays hires, introduces inconsistent evaluation criteria across recruiters, and prevents teams from responding quickly to strong candidates who may be interviewing with competitors.

When a new job application arrives in the applicant tracking system, the automation retrieves the resume and job description, then uses AI to extract the candidate's experience, skills, and education and the role's requirements, compare them, produce a fit score with an explanation, and write a short candidate summary. It updates the candidate record with skill tags, score, and summary, then routes by score band, moving strong fits to screening and notifying recruiters, sending borderline fits to manual review, and marking weak fits not qualified.

Strong candidates reach recruiters while they are still on the market, and every applicant is judged against the same criteria instead of whichever recruiter happened to read the resume.