What is resume screening? Your questions, answered

Resume screening is the step where someone reads every inbound resume, checks the must-haves for the role, and decides which applicants are worth a closer look. Done by hand it is slow and inconsistent, and strong candidates get missed simply because no one reached their resume in time. Prescreener does resume screening automatically: it parses every resume, applies the knockout and eligibility rules you set, asks role-specific screening questions, scores role-fit against your criteria, and ranks the inbound pile so recruiters review the top matches first. Candidates are told AI is used to screen their application, and a human makes every final call.

No. Prescreener takes the repetitive reading and triage off your recruiters' plates so they spend their time on the candidates who matter. It scores applicants against your criteria and ranks the pile for recruiter review with reasons and knockout flags. It never auto-hires or auto-rejects anyone. Every decision to advance, interview or pass stays with a human on your team. See how it works.

Before their application is screened, candidates are clearly told that AI is used to help screen resumes and asked for their consent. If a role uses screening questions, every applicant for that role answers the same ones, so no one is judged on who happened to review their file. Prescreener does not use facial analysis, voice analysis or personality pseudoscience. It scores resumes and screening answers against job-related criteria, nothing else. See the features.

Prescreener scores each applicant against the criteria you define for the role, which makes screening consistent and comparable across the whole pile. It is decision-support, not a verdict: every score carries a transparent reason tied to the criteria so your recruiters can check the reasoning. We do not claim perfect accuracy, and we do not use face reading or personality pseudoscience. Humans review the ranked pile and make the final decision.

Consistency is the point of running a structured screen. Every applicant for a role is evaluated against the same criteria and scored on the same job-related signals, which removes a lot of the inconsistency of reading resumes by hand. On Growth and above you get impact ratio reports by sex, race and ethnicity from a voluntary candidate survey, with the four-fifths rule marked, that you can share with your auditor, and we do not score appearance, name or personality. A human reviews the ranked pile and makes the final hiring decision, so the AI never has the last word.

Prescreener is a decision-support tool: it ranks and flags applicants, and a recruiter makes every hiring decision. Candidates are told that AI helps screen their application and give consent before they are screened. On Growth and above, applicants can answer a voluntary self-identification survey that is stored apart from their application and never scored, and you get impact ratio reports by sex, race and ethnicity and their intersection, with the four-fifths rule marked, as CSV and PDF. Those reports are data for your bias audit. The independent bias audit that NYC Local Law 144 requires is carried out by an independent auditor you engage, and compliance with EEOC rules and employment law stays with you as the employer, so confirm your obligations with your legal team. See how scoring works.

No. Prescreener ranks and flags applicants for recruiter review and never makes a sole automated rejection. When an applicant misses a knockout rule, it surfaces it as a flag for a recruiter to review, not an automatic no. A human on your team reviews the ranked pile and decides who advances, who to interview and who to pass on. The AI is decision-support, not autonomous hiring.

Candidates are told up front that AI is used to screen their application and asked to consent before resumes are processed. We use encryption in transit and at rest, least-privilege access, and your candidate data stays yours and is not sold or used to train models for other companies. Resumes, parsed data and scores are retained for the period you configure or that law requires, then deleted or anonymized. Connections to your ATS are scoped and revocable.

You pay a flat monthly fee based on active jobs, applicant volume and seats. Starter is $199 per month for up to 3 jobs and 1,000 applicants, Growth is $499 per month for up to 15 jobs and 5,000 applicants with ATS export and impact ratio reports for your bias audit, and Scale is $1,290 per month for up to 50 jobs and 25,000 applicants with integrations and custom criteria libraries. Enterprise is $2,490 per month for up to 200 jobs, 50,000 applicants and 50 seats with everything in Scale. Every plan is also sold yearly at half the monthly price. There is no free plan and no percentage of salary, just a predictable monthly fee. See pricing.

Yes. Prescreener is screening-first, not a full applicant tracking system, so it sits alongside Greenhouse, Lever, Workable and any ATS you already run. You define the role and criteria, it reads the inbound pile, and on Growth and above the ranked shortlist with scores, reasons and knockout flags exports back to your ATS so it stays the single source of truth. There is no rip and replace. See use cases.

Minutes. You define the role criteria and knockout rules, add any screening questions, and it starts reading the inbound pile the moment applications land. There is no long onboarding before you get value.

There is no free plan. The live demo on the homepage shows Prescreener parse, score and rank a sample pile, and after you choose Get started and confirm your work email you can rank up to 3 of your own resumes against your role once, at no cost, before you pay. With a plan you set up your first role criteria and knockouts, and Prescreener starts parsing every resume with candidate consent and AI disclosure, scoring role-fit and building a ranked pile with reasons and knockout flags for your recruiters to review, alongside the ATS you already use.

Volume is set by your plan rather than by any technical ceiling: 1,000 applicants a month on Starter, 5,000 on Growth, 25,000 on Scale, and 50,000 on Enterprise. Applications are read as they land instead of in an overnight batch, so a role that draws 400 applicants in its first 48 hours comes back ranked while the posting is still fresh. For context, a recruiter reading by hand manages roughly 20 to 30 resumes an hour before quality starts to slip.

It depends almost entirely on applicants per requisition. Below roughly 50 applicants a role, a recruiter can read the pile within a day or two and will usually make better calls than any scoring model, so the honest answer is no. Above a few hundred, the reading either does not happen properly or it consumes the recruiting hours you are paying for anyway. Work out your cost per requisition at current recruiter hourly rates and compare it against a flat monthly fee before you buy anything.

An applicant tracking system is a system of record. It stores candidates, moves them through stages, schedules interviews and holds the audit trail. Resume screening software evaluates: it reads each application against your criteria, scores role-fit and ranks the pile. Most ATS platforms include filters and keyword search but not scoring or ranking, which is why screening tools run alongside them rather than replacing them.

No, and we would advise against it. Prescreener is not a system of record and has no interest in becoming one, so nothing migrates and no historical data moves. It reads the inbound pile, ranks it, and on Growth and above exports the shortlist with scores, reasons and knockout flags back into the ATS your team already lives in. If you stop using it, your ATS is untouched, which is a large part of why buying a layer is a smaller decision than buying a platform.