AI-powered labor compliance screening in four steps. Search, screen, analyze with machine learning, and export enforcement data from OSHA, WHD, NLRB, and SEC EDGAR — unified through entity resolution into a single employer profile with predictive risk scoring.
LaborAudit unifies employment law enforcement data from four federal agencies and state attorneys general into a canonical employer graph with full SourceSeal data provenance.
From a simple employer name search to a complete cross-agency enforcement analytics report.
Enter any employer name. LaborAudit's entity resolution engine matches across name variations, DBAs, and subsidiaries to find all records — even when agencies use different names for the same company.
Try a free lookup →See the full cross-agency enforcement profile: WHD wage theft cases, NLRB unfair labor practice filings, OSHA safety inspections, SEC EDGAR corporate linkages, and state AG enforcement actions — all on one screen with SERI risk scoring.
View the dashboard →AI models predict which employers face enforcement next. AI risk scores trained on employers, anomaly detection for unusual enforcement clusters, AI-powered similarity search, and natural language queries across all datasets.
See plan features →Generate employer dossiers, CSV data exports, PDF reports, and CSDDD audit packages. Set up watchlist alerts to monitor employers for new enforcement actions automatically.
Compare export options →Supplier risk assessment and labor compliance screening for the professionals who need it most.
AI risk predictions identify employers likely to face enforcement next. Use cross-agency enforcement history as discovery material. OSHA citation patterns support class certification in wage-and-hour cases. Ask LaborAudit in plain English to surface patterns across datasets.
Map federal enforcement actions to GRI, SASB, UNGP, and CSDDD indicators. AI similarity search finds employers with matching compliance profiles for peer benchmarking. Screen supply chain partners with anomaly detection and generate ESG due diligence reports.
Batch screening across employers with AI-powered risk scoring. Uncover enforcement risk hidden in subsidiaries and DBAs. Insurance risk indicators (Workers’ Comp + EPL) quantify liability exposure before acquisition.
Anomaly detection alerts flag unusual enforcement clusters before they escalate. Benchmark industry enforcement rates, track violation trends, and set up watchlist alerts. Predictive risk scores prioritize compliance resources.
Labor compliance screening is the process of checking an employer's enforcement history across federal agencies — including OSHA workplace safety inspections, DOL Wage and Hour Division investigations, and NLRB unfair labor practice filings — to assess regulatory risk before hiring, investing, or entering a supply chain relationship.
LaborAudit indexes comprehensive OSHA inspection and violation data from the Department of Labor's enforcement database. Our entity resolution engine links OSHA records to the same employer across WHD and NLRB databases, giving you a cross-agency view that single-source lookups miss.
LaborAudit unifies five data sources: DOL Wage & Hour Division, NLRB, OSHA, SEC EDGAR, and state attorneys general enforcement actions. All data is linked through Bayesian entity resolution into a canonical employer graph with full SourceSeal data provenance.
Cross-agency enforcement data maps directly to ESG frameworks including GRI 403 (Occupational Health and Safety), SASB SV-HL-310 (Workforce Health & Safety), UNGP human rights indicators, and EU CSDDD adverse impact identification. LaborAudit maps enforcement actions to 43 ESG indicators across these four frameworks.
Yes. LaborAudit links SEC EDGAR Exhibit 21 subsidiary disclosures to enforcement records in WHD, NLRB, and OSHA. This reveals enforcement actions filed under subsidiary or DBA names that standard single-entity searches miss — critical for M&A due diligence and CSDDD compliance.
The Labor Enforcement Risk Score (LERS) is a 0–100 composite score with AAA-to-C ratings. The latest version uses machine learning trained on employer enforcement data with features that capture structural similarity across the employer network. The model achieves high accuracy for predicting future enforcement actions, combining violation severity, recurrence patterns, cross-agency breadth, penalty magnitude, and temporal trends.
LaborAudit uses multiple AI models: machine learning for predictive risk scoring, graph-based AI for employer similarity analysis, anomaly detection algorithms for enforcement pattern recognition, AI-powered semantic search across OSHA accident narratives, and AI for natural language queries. All models are trained on real federal enforcement data across employers.
LaborAudit uses graph-based AI trained on employers to capture structural compliance patterns—employers with similar enforcement histories, industries, and violation profiles cluster together. This powers the “Similar Employers” and “Enforcement Pattern Analysis” features, useful for supply chain peer analysis and insurance risk benchmarking.
From free enforcement lookups to full enterprise compliance packages — cross-agency enforcement analytics for every team.