Kreativs
Fair Hiring

The model cannot see age, gender, or ethnicity. By design.

We did not add bias mitigation on top of a biased model. We removed demographic data from the scoring pipeline entirely. The AI evaluates skills, experience, and career trajectory. Nothing else enters the equation. Ever.

Bias Analysis

Clean
Gender-Neutral Language

No gendered terms detected in job posting or evaluation criteria

Age-Neutral Criteria

Requirements focus on skills, not years of experience

Education Requirements

Consider if degree requirement excludes qualified candidates

Detecting All Forms of Bias

Our AI identifies and flags potential bias across the entire hiring lifecycle.

Job Description Bias

Detect gendered language, exclusive requirements, and coded language that discourages diverse applicants.

Evaluation Criteria Bias

Ensure scoring criteria are job-relevant and do not proxy for protected characteristics.

Resume Screening Bias

Blind screening options that hide names, photos, and other potentially biasing information.

Outcome Analysis

Statistical analysis of hiring outcomes to identify patterns indicating systemic bias.

Interview Process Bias

Structured interview guides and calibration for consistent, fair candidate assessment.

Affinity Bias Detection

Flag when evaluators may be favoring candidates similar to themselves.

Bias is caught before it affects a single candidate

Most platforms audit for bias after the fact. Kreativs prevents it in real time -- from the moment a job description is written to the moment an offer is sent.

  • Real-time feedback as you write job descriptions
  • Automatic flagging of potentially biased evaluation criteria
  • Blind resume review options for initial screening
  • Calibration tools for interview panels
  • Ongoing monitoring of hiring outcome patterns

Diversity Impact Report

Applied
42%+5%
Phone Screen
44%+8%
Interview
41%+3%
Offer
45%+12%
Hired
43%+10%

Underrepresented groups representation vs. industry benchmark

Try explaining a rejection to a candidate. Now you can.

Every score has a written assessment. Every rejection has a documented reason. Every decision is defensible to a candidate, a regulator, or a courtroom.

100% Explainable Scoring

Every candidate score comes with a detailed breakdown of exactly why they received that score.

Audit-Ready Documentation

Complete records of all decisions, criteria, and reasoning for EEOC and OFCCP compliance.

Human Override Always Available

AI makes recommendations, humans make decisions. Override any AI suggestion with documented reasoning.

AI Decision Breakdown

Technical Skills Match92%
Communication Assessment87%
Problem-Solving Aptitude95%
Cultural Contribution Potential88%

No demographic data included in scoring. All criteria are job-relevant.

Enterprise HR Teams

  • Organization-wide bias monitoring dashboards
  • EEOC and OFCCP compliance reporting
  • DEI goal tracking and progress measurement
  • Training resources for hiring managers

Recruiting Agencies

  • Demonstrate fair practices to enterprise clients
  • Diverse slate generation for client requirements
  • Documentation for client compliance needs
  • Differentiate with proven bias-free processes

See how bias-free evaluation works with your own data

We will run your job descriptions through our bias detection engine and show you how candidate scoring works without demographic data in the model.