Training Data for HR AI Models

Skip months of data labeling. Get pre-labeled synthetic employee data for attrition prediction, pay equity analysis, and workforce analytics.

Explore Training Data API See 43 ML Labels

The HR AI Data Problem

Real Employee Data is Off-Limits

Training ML models on actual employee records? Legal says no. GDPR, CCPA, and EEOC compliance make real HR data nearly unusable for AI.

Data Labeling Takes Forever

Building an attrition prediction model? You need labeled outcomes. Manually tagging thousands of records delays your project by months.

Public Datasets Are Too Simple

Kaggle's employee datasets have 10 fields and 1,000 rows. Real HR AI needs complex relationships and scale.

Synthetic Employee Data, Pre-Labeled for ML

Generate millions of synthetic HR records with 43 pre-computed ML labels. Built by HRIS experts, designed for data scientists.

43 Pre-Built ML Labels

Every record includes labels for flight risk, performance trajectory, pay equity gaps, promotion likelihood, and more. Ready for training.

Configurable Bias Injection

Testing fairness-aware models? Inject known biases (gender pay gap, age discrimination) to validate your model catches them.

Multi-Company Datasets

Train on data from 500 simulated companies. Model market dynamics, not just single-company patterns.

Scale to Millions

Generate 1M+ employee records for machine learning. Enough data to train deep learning models, not just toy examples.

43 Pre-Computed ML Labels

Every generated employee record includes these training-ready labels

Attrition & Retention

  • flight_risk_score
  • terminated_within_6mo
  • terminated_within_12mo
  • voluntary_termination
  • retention_risk_tier

Performance & Growth

  • performance_trajectory
  • promotion_likelihood_12mo
  • high_performer_flag
  • engagement_score
  • skill_gap_severity

Compensation & Equity

  • pay_equity_ratio
  • compa_ratio
  • underpaid_flag
  • salary_increase_due
  • total_comp_percentile

Workforce Analytics

  • manager_effectiveness
  • team_attrition_risk
  • succession_candidate
  • diversity_category
  • remote_work_suitability

+ 23 more labels included

HR AI Models You Can Build

Attrition Prediction

Train models to predict employee turnover using our attrition prediction dataset. Pre-labeled with terminated_within_6mo, flight_risk_score, and more.

Pay Equity Analysis

Build fair compensation models with our pay equity dataset. Includes known bias flags so you can validate your model detects discrimination.

Performance Prediction

Forecast employee performance trajectories. Labels include high_performer_flag, promotion_likelihood, and peer benchmarks.

Workforce Planning

Model headcount scenarios across simulated companies. Multi-company datasets let you train models that generalize.

vs. Public HR Datasets

Feature Kaggle / UCI Synthetic HRIS
Record count 1,000 - 15,000 Up to 1,000,000+
Fields per record 10-20 80+
Pre-computed ML labels 1-3 43
Multi-company data No Yes (up to 500)
Configurable bias injection No Yes
International data Usually US only 25 countries

Start Training Your HR AI Model

Free tier includes 10,000 labeled records. API access for automated pipelines.

Get Training Data