EU workforce intelligence and pay-transparency compliance platform for HR, people analytics, and strategy teams.
This system is described in:
Marti, S. V. (2026). Why Tight Labour Markets Do Not Close Gender Pay Gaps: Evidence from a 27-Country Eurostat Panel (2019–2024, 11 NACE sectors; r ≈ +0.44 employment–GPG correlation). MPRA: Paper No. 129330 | SSRN: abstract=6826361 | Zenodo: 10.5281/zenodo.20455974
Live dashboard: https://workforceguardai.souravamseekar.com/app · Research views: /app/research
Keywords: gender pay gap · pay transparency · EU Pay Transparency Directive ·
labour market tightness · Eurostat · composite indicators
Live at → workforceguardai.souravamseekar.com
| Command Centre — signal scores, executive brief, live market indicators | Market Intelligence — unemployment trend, vacancy by sector, gender pay gap charts |
 |
 |
| Compare — side-by-side country and sector benchmarking | Pay Analysis — company vs market pay gap with derived scores |
 |
 |
| Govern & Export — hash-chained audit log and compliance evidence pack | AI Analyst — natural language questions with grounded evidence |
 |
 |
WorkforceGuard turns public EU labour-market data and internal company payroll into decision-ready intelligence — with a full compliance audit trail built in.
- Labour market dashboard — employment rate, unemployment, job vacancies, and gender pay gap across all 27 EU member states and 13 NACE sectors, sourced directly from Eurostat
- Benchmark-aware analyst — ask natural-language questions; the copilot answers with grounded evidence, provenance citations, and benchmark context (prior period, EU average, or peer group)
- Country × sector comparison — side-by-side delta table with auto-generated narrative synthesis across any two geographies or sectors
- Pay transparency review — upload internal payroll; the platform blends it against market benchmarks and surfaces review items flagged under the EU Pay Transparency Directive
- Governance and audit log — every decision (approve, override, reverse, export) is written to a SQLite-backed hash-chained event log for legal-grade evidence packs
- Compliance evidence pack — one-click export of all metrics, provenance, and governance events as a structured bundle ready for regulatory filing
The EU Pay Transparency Directive (2023/970) requires member-state transposition by 7 June 2026 and employer reporting from June 2027 (≥250 employees). CSRD and Article 9 SFDR impose parallel workforce disclosure obligations. WorkforceGuard is designed specifically for this compliance surface — not generic HR analytics.
Eurostat API ──► Python ingestion ──► DuckDB ──► dbt models
│
Internal payroll (CSV/upload) ─────────┘
│
FastAPI service
│
React + Vite dashboard
Data layer: Eurostat LFS, JVS, and SES ingested as Parquet → staged and modeled in dbt (staging → core marts → internal marts → public company benchmarks) → served via DuckDB at query time, no database server required.
API layer: FastAPI with a single AnalyticsRepository that resolves filters, computes metrics, assembles evidence bundles, and writes governance events. Deployed on GCP via Docker.
Frontend: React 18 + TypeScript + Vite, TanStack Query for data fetching, Recharts for time-series visualisation, Tailwind CSS. Deployed on Vercel.
CI/CD: GitHub Actions — PRs and pushes to main run CI (pre-commit hooks, tests, lint, frontend production build, secret scan). Deploy to GCP and Vercel runs only after CI passes on main. Releases are SemVer Git tags (vX.Y.Z) with GitHub Releases. Git and release process: CONTRIBUTING.md.
| Source | Dataset | Coverage |
|---|---|---|
| Eurostat Labour Force Survey | Employment rate, unemployment rate, gender pay gap | EU27, 2019–2024 |
| Eurostat Job Vacancy Statistics | Job vacancy rate by sector | EU27, quarterly |
| Eurostat Structure of Earnings Survey | Pay gap by sector and occupation | EU27 |
| EGAPro (France) | Company-level gender pay index | French listed companies |
| UK Gender Pay Gap Service | Company GPG disclosures | UK listed companies |
Hash-chained governance log — audit events are chained by SHA-256 so any tampering is detectable. The chain integrity status is shown in the dashboard and verified on every API call.
Evidence provenance on every metric — every number displayed traces back to its Eurostat source ID, dataset version, formula version, and whether human review is required. This is structural, not cosmetic.
Benchmark-aware copilot — the analyst endpoint selects the appropriate benchmark basis (prior period / EU average / peer group) based on data coverage, then wraps every answer with the benchmark confidence and a coverage note. It refuses to answer confidently when coverage is partial.
dbt layered modeling — staging → core → internal → public company mart separation means the EU reference layer and company-specific layer are independently testable and replaceable.
Prerequisites: Python 3.11+, Node 20+, dbt-duckdb.
CI uses Python 3.12 and Node 22. Env templates: .env.example.
Versioning: SemVer — CONTRIBUTING.md. Current: v0.1.0.
# Clone
git clone https://github.com/SVamseekar/workforceguardai.git
cd WorkforceGuard-AI
# Backend
pip install -r dashboard/backend/requirements.txt
cd dashboard/backend && uvicorn main:app --reload --port 8000
# Frontend (separate terminal)
cd dashboard/frontend && npm install && npm run dev
# → http://localhost:5173To run the dbt models against local data:
cd analytics
dbt run
dbt testPython FastAPI DuckDB dbt Parquet React TypeScript Vite TanStack Query Recharts Tailwind CSS Docker GCP Vercel GitHub Actions
MIT. See LICENSE.