🇦🇷 Open GovTech · Argentina

Algorithmic monitoring of the
Argentine State — in real time

7 independent monitors. 3 branches of government. 1 composite risk index. Official public data only. Open source.

🚀 Open Platform 📡 API Docs ⭐ GitHub
7
Active monitors
3/3
Gov. branches
1,154
Officials tracked
1,839
Contracts
$3.8B
ARS monitored
Methodology

The Institutional Risk Index (IRI)

A composite score that aggregates four weighted dimensions of institutional risk across all government branches. Every alert is explainable — not a black box.

35%

Financial Risk

Anomalies in budget execution, payment flows, and treasury operations
30%

Procurement Risk

XAI-powered detection of irregular patterns in public tenders and contracts (COMPR.AR + BORA)
20%

Operational Risk

Absenteeism, productivity, and institutional performance metrics
15%

Data Risk

Quality, completeness, and timeliness of published public information
Monitors

All three branches of government

All monitors are live and updated daily from official sources.

⚡ Executive

Executive Monitor

Chief of Staff Office · SGP · Presidency · Payroll · Alerts
⚡ Executive

Contracts Monitor v1

COMPR.AR · National Treasury · Real-time risk analysis
⚡ Executive

Contracts Monitor v2

BORA + COMPR.AR · XAI irregularity detection
🏛️ Legislative

Deputies Monitor

Attendance · Productivity · Cost per capita · ICE index
🏛️ Legislative

Senate Monitor

Participation · Party reports · Performance indicators
⚖️ Judicial

Judicial Monitor

Supreme Court · Judiciary Council · Federal courts · IRA
🚦 Cross-branch

IRI Dashboard

Composite institutional risk score · Central dashboard
Technology

Open source stack

Built with Python and FastAPI. Deployed on Railway. Data fetched daily from official Argentine government APIs.

Python 3 FastAPI 0.115 Uvicorn 0.30 HTTPX 0.27 Railway Swagger UI XAI / Explainable AI JGM Open Data COMPR.AR BORA CSJN
Author

About the researcher

VM

Ph.D. Vicente Humberto Monteverde

Doctor in Economic Sciences · Researcher in political economy and corruption phenomena.
Author of the Regressive Income Transfer theory and developer of the XAI algorithm applied to public procurement analysis.
Published in Journal of Financial Crime (Emerald Publishing). Advisor on transparency and algorithmic auditing of public spending.

vhmonte@retina.ar

Disclaimer: This tool is experimental and academic in nature. Results are algorithmic risk indicators — they do not imply legal judgment, accusation, or determination of responsibility regarding any company, institution, or individual. The goal is to promote transparency and informed public debate about government spending.