Consistent evaluation criteria
When every candidate answers the same structured questions, you compare apples to apples. Resume screening varies by reviewer and keyword choice; structured interviews apply the same bar to everyone.
Understand how resume screening works, where it falls short, and how structured AI interviews give you a fuller picture of every candidate.
Resume screening is the process of reviewing job applications and CVs to identify candidates who meet the minimum qualifications for a role. Recruiters—or automated tools—scan resumes for keywords, credentials, and experience before deciding who advances. While it narrows a large applicant pool quickly, it only reflects what candidates write, not how they communicate, reason, or fit the role in practice.
For most teams, resume screening is the first filter in the hiring funnel. A job posting can attract dozens or hundreds of applicants, and manually reading every CV is time-consuming and inconsistent. Automated applicant tracking systems (ATS) help by scoring resumes against keywords, but they share the same fundamental limitation: a resume is a self-reported document. It tells you what someone has done on paper—not whether they can actually do the job. Criba extends screening beyond the resume with a short, structured AI voice interview that every candidate completes on their own schedule, giving you comparable signal across the full applicant pool.
When every candidate answers the same structured questions, you compare apples to apples. Resume screening varies by reviewer and keyword choice; structured interviews apply the same bar to everyone.
Reading and scoring hundreds of resumes takes days. A structured AI interview runs asynchronously—candidates complete it on their schedule and results are ready before your next morning stand-up.
Applicants routinely stuff resumes with keywords to pass ATS filters. A short spoken interview makes it much harder to fake competence, surfacing candidates whose skills are real.
Criba's Pass / Borderline / Reject shortlist links every score to direct candidate quotes, so your team can audit and override decisions with full context—not just a number.
Every applicant gets a chance to speak for themselves beyond their CV. That levels the field for strong candidates whose resumes undersell their actual ability.
Criba is not a replacement for your full hiring stack. It solves the screening bottleneck specifically, fitting into the workflow you already have rather than demanding a rip-and-replace.
Job posting and application collection
A recruiter publishes a role with required qualifications. Applicants submit resumes (and sometimes cover letters) through a job board or careers page, which are collected in an ATS or inbox.
Filtering against criteria
Manually or via ATS keyword rules, each resume is scanned for education, years of experience, specific skills, and other requirements. Applications that don't meet the threshold are rejected; the rest advance.
Recruiter review of shortlisted resumes
A human recruiter reads the remaining CVs in detail, comparing candidates and flagging the most promising profiles for a phone screen or next interview stage.
Handoff to interviews
Candidates who pass resume review are invited to a phone screen or first-round interview. At this point, most teams meet the candidate for the first time and discover whether the resume matched reality.
The terms are used interchangeably. 'Resume' is the preferred term in North America; 'CV' (curriculum vitae) is more common in Europe and Latin America. Both refer to the document a candidate submits summarizing their work history, education, and skills. The screening process is the same regardless of which term you use.
Resume screening can only evaluate what a candidate chooses to write. It misses communication skills, reasoning ability, and cultural fit. Keyword-based ATS filters reject qualified candidates whose resumes use different terminology. Implicit bias can also influence how reviewers interpret the same resume, leading to inconsistent outcomes across the applicant pool.
Automated ATS resume scoring is fast but imperfect. It excels at filtering for hard requirements like certifications or minimum years of experience. It struggles with nuance—two candidates with equivalent skills but different resume formats may receive very different scores. Combining resume screening with a structured interview step significantly improves accuracy.
Criba adds a ~5-minute structured AI voice interview after the resume step. Every candidate answers the same questions, and the output is a ranked Pass / Borderline / Reject shortlist tied to direct candidate quotes. This gives your team comparable, auditable signal that a resume alone cannot provide—without adding recruiter workload.
Manual resume screening typically takes 6–10 seconds per resume for an initial pass, and several minutes for a detailed review. For a 200-applicant role, a thorough manual review can take 4–8 hours. Automated keyword screening is near-instant but requires upfront configuration and regular tuning to avoid high false-positive and false-negative rates.
No. Criba is designed to work alongside your existing process, including any ATS you already use. Most teams still apply basic resume filters for hard requirements, then use Criba's structured AI interview to evaluate the candidates who pass that initial bar. Criba solves the screening bottleneck; it does not replace recruiter judgment.