The agentic AI hiring platform redefining how you hire

    Screenr is an all-in-one AI hiring platform built to help you screen, verify, and engage talent 10x faster with agentic AI.

    Resume screening is broken.

    Traditional screening tools weren't built for modern hiring. They match keywords instead of understanding candidates.

    Resumes are inflated

    Candidates exaggerate skills and experience. Without proper screening, you're hiring based on claims.

    Manual resume screening takes forever

    Reviewing hundreds of resumes manually is slow, tedious, and leads to recruiter burnout.

    Keyword matching fails

    Traditional ATS tools match keywords, not actual skills. Great candidates get filtered out.

    Costly hiring mistakes

    Bad hires cost 30% of annual salary. Most are preventable with better screening.

    HOW VERIX WORKS

    From Application to Ranked Results

    Your AI agent Verix handles the entire pipeline autonomously — candidates apply through a link, and Verix screens, verifies, tests, interviews, and ranks them.

    Apply

    via Link

    Review

    Inbound Applicants

    Spot

    Fraudulent Resumes

    AI

    Screening

    Skill

    Verification

    Verix

    Engages

    Ranked

    Results

    0

    Applications

    0

    Screening

    0

    Top Candidates

    STEP 01

    Candidates Apply Through Your Link

    Share a unique application link for each job. Candidates submit their resume and details — Verix takes it from there. No manual intake needed.

    screenr.co/apply/senior-dev-acme

    Full Name

    Sarah Chen

    Resume

    sarah_chen_resume.pdf

    LinkedIn

    linkedin.com/in/sarahchen

    Submit Application
    STEP 02

    AI Resume Screening & Fraud Detection

    Verix instantly parses resumes, extracts skills, and flags inconsistencies. It goes beyond keywords — understanding experience depth, career trajectory, and red flags.

    SC

    Sarah Chen

    Full-Stack Developer

    Best Match
    Experience
    Location
    Education
    Skill

    Skill Highlights

    ReactNode.jsPostgreSQLAWSTypeScript
    No inconsistencies detected
    STEP 03

    Verix Sends Custom Screening Forms

    After screening resumes, Verix automatically generates and sends role-specific assessment forms to shortlisted candidates — testing technical depth and problem-solving.

    Verix Auto-Generated Assessment

    Q1: System Design

    "Design a real-time notification system that handles 10K concurrent users..."

    Q2: Debugging

    "Given this API response pattern, identify the performance bottleneck..."

    Q3: Code Review

    "Review this React component and suggest improvements for..."

    Sent to 12 shortlisted candidates
    STEP 04

    Verix Engages & Ranks Candidates

    Verix engages with candidates in the background — following up, collecting responses, scoring assessments — and produces a final ranked list with explainable scores.

    Verix Engagement Complete

    #1
    SC

    Sarah Chen

    94%Strong
    #2
    AR

    Alex Rivera

    87%Good
    #3
    JP

    Jordan Park

    72%Moderate
    FEATURES

    AI Resume Screening Powered by Multi-Layer Intelligence

    Four interconnected AI systems work together to deliver automated resume shortlisting and the most thorough candidate evaluation in the industry.

    AI Resume Screening

    Goes beyond keyword matching — understands context, career progression, and skill relevance

    Contextual skill extraction
    Experience depth analysis
    Education relevance scoring
    Red flag detection

    Link & Profile Verification

    Verifies every claim on the resume by cross-referencing external profiles and public data

    LinkedIn profile verification
    GitHub contribution analysis
    Portfolio link validation
    Inconsistency detection

    Skill Verification Tests

    Custom screening questions generated by AI, precisely tailored to each role's requirements

    Role-specific question generation
    Technical depth assessment
    Soft skill evaluation
    Anti-cheating measures

    AI Candidate Engagement

    Verix autonomously engages with candidates — sending assessments, collecting responses, and following up in the background

    Auto-sends assessments
    Response quality analysis
    Follow-up engagement
    Standardized scoring
    AI DEEP DIVE

    How Our AI Ranking Actually Works

    Not a simple keyword match — a multi-dimensional intelligence engine that evaluates candidates across four critical layers.

    L1

    Resume Analysis

    Weight: 30%

    Skills match, experience relevance, education fit, career trajectory

    L2

    Verification Score

    Weight: 25%

    Link authenticity, profile consistency, claim validation, public data cross-reference

    L3

    Screening Performance

    Weight: 25%

    Test scores, response quality, technical depth, problem-solving ability

    L4

    Engagement Score

    Weight: 20%

    Assessment responses, follow-up quality, candidate responsiveness, overall engagement

    The Result: A Holistic, Trustworthy Score

    By combining all four layers, Screenr produces a composite candidate score that goes far beyond what any human screener — or keyword-based tool — could evaluate in the same time. Every score is explainable, auditable, and backed by verifiable data.

    EXAMPLE OUTPUTS

    See What Screenr Delivers

    Real example outputs from our AI screening pipeline — the depth and clarity your team gets on every candidate.

    CANDIDATE SCREENING REPORT

    SC

    Sarah Chen

    Senior Full-Stack Developer

    92%

    Overall Score

    Skills Match95%
    Experience88%
    Verification90%
    Engagement94%
    LinkedIn Verified
    GitHub Active
    Portfolio Valid

    AI SUMMARY

    Strong full-stack developer with 5 years of experience. Verified GitHub shows consistent contributions across React, Node.js, and PostgreSQL. Excels in system design and demonstrates strong problem-solving in technical screening.

    No red flags detected

    COMPARATIVE RANKING VIEW

    Senior Full-Stack Developer

    4 candidates ranked

    #1
    SC

    Sarah Chen

    94%

    Strong Match
    #2
    AR

    Alex Rivera

    87%

    Good Match
    #3
    JP

    Jordan Park

    72%

    Moderate Match
    #4
    SW

    Sam Wilson

    58%

    Weak Match

    10x

    Faster Screening

    vs. manual review

    95%

    Accuracy

    in skill matching

    100+

    Companies

    trust Screenr

    50K+

    Candidates

    screened by AI

    FAQ

    Frequently Asked Questions

    Common questions about how Screenr works, data privacy, and our AI ranking system.

    Ready to Let AI Handle Your Hiring?

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