Civic Intelligence Platform

PGŽ Public Finance — transparent, verifiable, optimised

From budget data to tangible savings: AI anomaly detection, execution forecasting and operational process optimisation for Primorsko-goranska županija (PGŽ).

576+

Javnih tijela u RH

+12%/god

Prosj. rast proračuna JLS

2,5%

Ušteda — Base scenario

30 dana

Pilot angažman

PGŽ Budget — Overview 2023–2026

All figures drawn from official PGŽ sources. Click the icon to view the source.

Konsolidirani proračun 2023

2023

224,2 mil. €

Konsolidirani proračun 2024 — rebalans

2024

295 mil. €

Konsolidirani proračun 2025

2025

353,1 mil. €

Proračun 2026

2026

406,9 mil. €

Rast proračuna PGŽ 2023–2026

2026

+81,5%

2023–2026SKUPSTIN

Napomena: Konsolidirani proračun obuhvaća sve proračunske korisnike — škole, bolnice, komunalna i javna poduzeća. Platforma je primjenjiva na sve razine javnog sektora u Republici Hrvatskoj.

How Savings Are Generated

A transparent, reproducible model built on verified data.

PROJEKCIJA — godišnje uštede

~407 tis. €~5,09 mil. €/god.

Konzervativni (10% × 1%) do naprednog scenarija (25% × 5%). Pretpostavke na /methodology.

PROJEKCIJA
01

Measurement

Automated ingestion of budget data from CKAN, OpenCity and MFin portals. Standardisation according to the GFI chart of accounts.

02

Detection

A Z-score statistical model identifies deviations from expected execution. Thresholds: |z| ≥ 2.0 (high), |z| ≥ 3.0 (critical).

03

Forecasting

Linear extrapolation model with a 95% confidence interval for end-of-year (EOY) execution. Phase 2: Prophet / LSTM.

04

Action

Prioritised list of anomalies and recommendations for management. Citizen dashboard for transparency.

AI/ML/RL in Practice — PGŽ Context

Four concrete modules with verified applications and measurable outcomes.

AKTIVNO

Budget Control Tower

Centralizirani nadzor proračunskog izvršenja, KPI monitoring i automatski alerting za sve stavke i razine. Anomalije prikazane u realnom vremenu.

AKTIVNO

Anomaly Detection

Z-score statistički model identificira neobična odstupanja izvršenja od bazne linije. Prag: |z| ≥ 2,0 (high), |z| ≥ 3,0 (critical).

AKTIVNO

EOY Forecasting

Prognoza godišnjeg izvršenja (end-of-year) na temelju trenutnih trendova. Linearni model s 95%-tnim intervalom pouzdanosti. Phase 2: Prophet / LSTM.

PHASE 2

Operational Optimization

Optimizacija komunalnih usluga — rute, raspored, potrošnja resursa. Reinforcement Learning modul za kontinuirano unapređenje operativa.

Pilot in 30 Days

A structured, low-risk onboarding process with clear deliverables for each week.

Tjedni 1–2

Onboarding & ingestija

Pristup podacima, setup data warehousea, automatski ingest CKAN / OpenCity izvora.

Tjedni 3–4

Detekcija & dashboardi

Aktivacija anomaly detection modela, prvi BI dashboardi s KPI prikazom i anomaly alertingom.

Tjedni 5–6

Prognoze & validacija

EOY forecast modeli, backtesting na prethodnim podacima, validacija s naručiteljem.

Tjedan 7

Predaja & prezentacija

Konačni izvještaj, prezentacija nalaza upravi, preporuke za fazu 2 i skaliranje.

Pilot — 30 dana — besplatno

Ready for Transparency

First demonstration on your own data within 30 days. No cost, no vendor lock-in.

Projection based on the savings model. Assumptions and methodology are available on the Methodology page. Actual results depend on data quality and operational implementation.