Prescreener
How it works
ATS screening Resume parser Candidate screening software AI recruiting software AI applicant screening Resume ranking software Bulk resume screening Tech hiring Retail hiring Healthcare hiring Sales hiring Customer service hiring See all →
BambooHR alternative Fountain alternative Workday alternative iCIMS alternative HireVue alternative CVViZ alternative Sapia.ai alternative Manatal alternative Workable alternative Greenhouse alternative Lever alternative SmartRecruiters alternative JazzHR alternative Paradox alternative Ashby alternative Breezy HR alternative Eightfold alternative hireEZ alternative Pinpoint alternative
Pricing Blog

AI screening · AI resume screening

AI resume screening software for AI candidate screening at volume

Most tools that call themselves AI resume screening are doing keyword matching with a better interface. You can tell within one demo. Hand them a career changer, a veteran whose resume is written in military job codes, or a strong operations manager whose title happens to be "coordinator", and a keyword filter buries all three while promoting whoever copied the job description into their skills section. The applicants who game the format win, and the applicants who can do the job do not.

Parse · score · rank · recruiter reviews

Shortlist Desk
Criteria

top · held

Screen the pile to watch Prescreener parse every resume, apply your criteria and knockouts, and rank the inbound applicants with a transparent reason on each.

Live, interactive · AI assists, you decide · no signup needed

top matches surfaced held for review Reasons on every card

AI assists · you decide · bias-audited (EEOC / NYC Local Law 144)

CONSISTENT CRITERIA RANKED PILE ATS-READY

Human-in-the-loop you decide

EEOC and LL144 bias-audited

Prescreener reads the resume rather than scanning it for strings. It pulls out what someone actually did, how long they did it, and at what scale, then checks that against the criteria you set for this specific role: the hard eligibility gates, the experience that genuinely predicts performance, and the screening questions you would have asked on a phone screen. Every applicant comes back with a role-fit score, the criteria they met and missed, and a short written reason a hiring manager can read and argue with. The pile arrives ranked, so recruiters start at the top instead of at whoever applied first.

The part worth being blunt about is what the AI is not allowed to do. It never rejects anyone. It ranks and flags, and a recruiter makes every accept or reject decision, because an automated employment decision tool that cannot explain itself is a liability no matter how good its scores look. Criteria are applied identically to every applicant, AI use is disclosed to candidates, and results are bias-audited to support EEOC standards and NYC Local Law 144. It runs alongside Greenhouse, Lever, Workable, or whatever ATS already holds your requisitions.

Why it works

What your team gets with AI resume screening

Reads meaning, not keywords

The model works from what a candidate did and at what scale, so a warehouse supervisor who never wrote the phrase "inventory management" is still scored on having run it for four years. Keyword filters miss exactly these people, and they are usually the ones worth calling.

A written reason on every candidate

Each ranking carries the criteria met, the criteria missed, and the evidence from the application behind both. That is what makes a score reviewable by a hiring manager, and it is what you need if anyone ever asks you to justify a screening decision.

Ranks, never rejects

Applicants who miss a hard requirement drop down the list with the reason attached rather than disappearing. A human makes every call. This is the single biggest difference between a defensible screening process and a black box.

What it handles

Parsed, scored and ranked on autopilot

Prescreener reads every inbound resume, applies your knockout and eligibility criteria, asks the screening questions you set, scores role-fit against consistent criteria, and ranks the applicant pile so your recruiters review the top matches first.

  • Reads every inbound resume within minutes of it arriving
  • Scores role-fit against the criteria you set per requisition
  • Asks your screening questions and checks the answers
  • Ranks the pile with the reasoning written under each candidate
  • Runs alongside your existing ATS instead of replacing it
  • Bias-audited to support EEOC standards and NYC Local Law 144
SHORTLIST Screening
#1 Maya R. 92
#2 Devon L. 88
#3 Priya S. 81 Review
Role-fit scored 48 screened this week

Why Prescreener

One step that screens the whole inbound pile

Not a full ATS, not a six-figure assessment suite, and not a staffing agency. Parse, score, rank and hand off in one place, shaped to the criteria you already hire on.

Reads every resume

Prescreener parses every inbound application, applies your knockout and eligibility criteria, and asks the screening questions you set. Applicants consent and are told AI is screening their application, so no qualified person sits in a backlog for days.

Scores role-fit consistently

Every applicant is scored against the same criteria, with a transparent reason on each candidate, so the pile is compared consistently and the scoring stays bias-audited against EEOC guidance and NYC Local Law 144.

Ranks the pile

The strongest matches rise to the top of a ranked pile your recruiters review first. Prescreener never auto-rejects, it ranks and flags candidates for review, and your team makes every decision.

Good questions

Questions about AI resume screening

AI resume screening software reads inbound resumes, extracts what a candidate has actually done, compares it against the criteria set for a role, and ranks applicants so recruiters review the strongest matches first. The useful versions score role-fit rather than keyword overlap and show the reasoning behind each candidate. The weak ones are keyword filters with a modern interface.
Accuracy depends almost entirely on the criteria you give it, not on the model. Criteria that name a concrete, checkable requirement produce consistent results; vague criteria like "strong communicator" produce noise no matter what technology reads them. The honest test on any demo is to hand the vendor twenty resumes you have already screened, including two you rejected and two you would hire, and read the reasons it gives.
Prescreener never auto-rejects. It ranks and flags, with the reason attached, and a recruiter decides. Some tools do auto-reject on knockout answers, which is worth asking about directly before you buy, because one badly worded question then removes qualified applicants with nobody reviewing the outcome.
Yes, and it is regulated. Disparate impact liability under Title VII, the ADEA, and the ADA applies to an algorithm exactly as it applies to a person, NYC Local Law 144 requires an independent bias audit and candidate notice, and several states have added their own rules. Litigation against screening vendors is active, so keep criteria job-related, disclose AI use, audit for adverse impact, and keep a human in the decision.
Any screening process can be biased, including a human one. A model trained on past hiring decisions can learn the patterns in those decisions, which is why criteria-based scoring, published bias audits, and visible reasoning matter more than the underlying technology. Ask any vendor for selection rates by group and for a per-candidate explanation. If they cannot produce either, that is the answer.
Most ATS platforms add AI where their structured data already lives, which is after a candidate has been advanced into a stage: scorecards, interview notes, summaries. The unread inbound pile in front of that pipeline is a different job. Prescreener works on the raw applications as they land and hands the ranked result back, which is why teams run it alongside an ATS rather than instead of one.
They overlap and most buyers use the terms interchangeably. In practice, resume screening describes reading and scoring the document itself, while applicant screening covers the whole applicant record including screening question answers and eligibility gates. Prescreener does both in one pass, and our applicant eligibility screening page goes deeper on the gates specifically.
Applications are read as they arrive rather than in a nightly batch, so a posting that collects 400 applicants over a weekend is already ranked when someone opens it on Monday. The practical limit stops being reading time and becomes how many candidates your team can interview, which is a better problem to have.
Read every resume screening question

Explore more

More ways hiring teams screen with Prescreener

Applicant tracking system screening

The AI screening layer that ranks your inbound pile alongside your ATS.

Learn more

Resume parser

A resume parser that does not stop at fields. It scores and ranks too.

Learn more

Candidate screening software

Screen every candidate on consistent criteria, then review the top matches.

Learn more
See every screening use case See pricing Back to resume screening

Stop reading the inbound pile by hand. Put screening on autopilot.

Set your role and criteria and Prescreener parses every inbound resume, scores role-fit, and ranks the pile for your team. Prescreener ranks and flags candidates, your recruiters make every hiring decision.

See pricing

Consistent criteria · bias-audited to EEOC and LL144 · human-in-the-loop