PLATFORM

Better hiring science means better hiring results.

One thread. Every product. Validated science throughout the hiring process.

1,300+

Validation studies for accuracy

2,000+

Calibration and fairness studies

75+

Peer-reviewed publications

20+

Years of I-O psych experience

250M

Assessments and interviews complete

Automation without validation is a liability.

Decisions based on science are more predictive and defensible.

Tech-only vendors

Hirevue

Focus

Features with unknown value (e.g., avatars)

Measuring improved outcomes (e.g., quality of hire and retention)

Value

Fast decisions

Accurate decision support at enterprise scale

Platform

Experience only

Experience + support on what and how to ask (content)

Process

Fully flexible

Customization inside a best practice framework

Compliance

Recruiter trust. Undocumented AI behavior.

Governed process. Legally defensible on published proof.

Improved performance, retention, and fairness from 250M+ interviews and assessments complete

Quality of hire impact in early careers / graduate

+3x

Candidates who score high are more than 3x as likely to receive high overall performance ratings.

Overall performance rating

New hire retention % over 180 days

Retention Impact in retail

+33%

Difference in retention between best and worst-fit candidates (based on 975,000 retail associate hires)

No significant adverse impact observed by age

Fairer

The 4/5th adverse impact measure means a measure is fair if the target group’s hiring rate is not below 80% of the highest group rate

Overall performance rating

Ethics and compliance

Industry-leading AI ethics and defensible compliance

01

AI Informs.
Humans decide.

Every score helps inform recruiter decisions.

Candidates can opt out.

Recruiters always make the final call.

02

Validated before deployed

Every model passes adverse impact testing before going live.

Annual independent audits

Ongoing monitoring per customer

03

Explainable, not a black box

Scores tied to behavioral anchors (BARS)

Rigorous explainability

Grounded in evidence not opaque predictions

04

Transparent to all stakeholders

Candidates grant AI consent

Legal gets audit docs

IT gets full AI disclosure

How it works: Different types of hiring science tests at multiple steps, not just at the end

Governed controls

Does it stay within approved boundaries?

Hiring
science framework

Identifies job relevance

Does it identify job-relevant skills that actually matter?

Validity of evaluation

Does it evaluate evidence accurately?

Reliability of interaction

Does it gather evidence safely and consistently?

AI Interviewer example: Only vendor to publish performance validations on sub-agents

1

Job relevance

→ Job description-to-script agent

Our research shows that the agent understands what matters for the job, asks the right questions, and catches questions that might be unfair.

2

Reliability of interaction

→ Conversation agent

Scientific validation confirmed that the agent interviews every candidate in the same, fairer way while helping them explain their experience.

3

Validity of evaluation

→ Scoring agent

Our validation study found that the agent scores candidates using the right job rules and gives similar answers the same score, no matter who the candidate is.

4

Governed controls

→ Guardrail agent

Our sciences proves that the agent follows the rules, records what it does, and continues working correctly when the system changes.

Large selection science team leading for over 20+ years

Mike Hudy

Chief Science Officer

As Chief Science Officer at Hirevue, Mike Hudy helps shape a science-led approach to skills-based hiring. An occupational psychologist with more than 25 years in the field, he has publicly emphasized structured, transparent hiring methods, stronger measurement of quality of hire, and AI systems grounded in validation research and post-hire outcomes rather than signals alone. He is also a co-author of Decoding Talent, a book on using AI and big data to improve hiring decisions.

Former Roles

Chief Science Officer, Modern Hire; EVP of Science at Shaker International, which he helped found; Senior Consultant, CEB/SHL; Training Evaluation Analyst, Nationwide Insurance.

Published Work

Co-author of Decoding Talent: How AI and Big Data Can Solve Your Company’s People Puzzle, a book advocating more scientific, data-backed, and less biased talent decisions

Leads over 30 hiring scientists on staff

Hirevue has IO Psychologists on the product, customer success and professional services team making sure development is based on research and rigorous testing.

Frequently asked questions

Hirevue evaluates candidates using job-relevant skills, behaviors, and competencies defined for a specific role. Depending on the solution, candidates may complete structured interviews, assessments, or job simulations designed to measure those capabilities consistently. Evaluation criteria are established for the role rather than applying one universal Hirevue score to every candidate.

Hirevue’s AI evaluates candidate responses against job-related competencies and defined evaluation criteria. For AI-scored video assessments, Hirevue analyzes the transcript of what a candidate says—not facial expressions, body language, appearance, background, or tone of voice. The goal is to provide recruiters with structured, job-relevant information to support hiring decisions.

No. Hirevue does not use facial analysis to evaluate candidates in its assessments. AI-scored responses are based on the content of a candidate’s answer and its relationship to relevant job competencies—not facial expressions, body language, appearance, or other visual characteristics.

Hirevue’s science team includes I-O Psychologists and Data Scientists who evaluate assessment models for job relevance, consistency, and potential demographic differences. Models are tested before deployment and monitored over time, with additional oversight provided through documented AI governance practices and independent audits.

Hirevue applies established principles from I-O Psychology, psychometrics, and data science to determine whether assessments measure job-relevant capabilities and support meaningful hiring decisions. Assessments and models are tested and validated before deployment, with ongoing monitoring designed to maintain consistent and defensible results.

Hirevue uses integrity and fraud-detection measures appropriate to different assessment and interviewing experiences. These may include signals that help identify potentially suspicious activity or inconsistencies for further review. Rather than treating a single signal as automatic proof of cheating, these tools are designed to give hiring teams additional information they can evaluate as part of the broader hiring process.

Hiring science applies research, data, and established principles from fields such as I-O Psychology and psychometrics to understand which candidate characteristics are relevant to success in a role. It helps organizations move beyond subjective hiring signals by creating structured, job-relevant ways to evaluate skills and competencies.

Structured hiring helps create a more consistent process by evaluating candidates against the same job-relevant criteria. Hirevue combines structured assessments with testing and monitoring designed to identify potential demographic differences, helping organizations make decisions based more on demonstrated skills and competencies and less on subjective signals.

No. Hirevue’s AI is designed to support human decision-making, not replace it. AI can help organizations evaluate job-relevant information consistently and give recruiters structured insights, while employers remain responsible for determining how those insights are used and for making hiring decisions.

Hirevue’s I-O Psychologists apply research on human behavior, work, measurement, and assessment to the hiring process. They help identify job-relevant competencies, develop and validate assessments, evaluate fairness, and ensure hiring technology is grounded in established scientific principles rather than relying only on technical capabilities.