NovaGovAI provides Philippine local government units, city planning offices, and national agencies with an AI-augmented decision intelligence platform — unifying CLUP data, zoning ordinances, NAMRIA geospatial layers, and inter-agency datasets into compliant, audit-ready analysis aligned with RA 7160 and DHSUD national land use policy.
From BARMM to Metro Manila, local government units are adopting AI-driven planning to close infrastructure gaps, reduce poverty, and deliver services faster — all grounded in real Philippine data.
This is the actual NovaGovAI interface. Search any Philippine city or province, explore data layers, click zones on the map, and ask AI anything about your LGU.
In November 2025, Naga City secured a ₱6.79M DEPDev grant and became the first LGU in the Philippines to deploy an AI-powered city planning system — integrating PHIVOLCS, MGB, DPWH, and NAMRIA data into real-time, predictive governance. Their AI command center now handles flood forecasting, traffic analysis, and hazard screening in seconds — tasks that take most LGUs weeks to complete manually.
Manage users, monitor agent activity, review reports, and configure data sources — all from a single secure dashboard built for LGU administrators.
Watch NovaGovAI's 14 AI agents process real Philippine data across 1,632 LGUs — simultaneously. Click any node to inspect its intelligence feed.
From CLUP preparation to disaster risk zoning, NovaGovAI integrates your LGU's spatial, demographic, and regulatory data — and turns it into decisions aligned with national land use policy and HLURB/DHSUD standards.
Based on live PSA 2023, DPWH, PNP, and DepEd national datasets — with conservative 15–50% AI-driven improvement rates applied to verified annual baselines.
From road deaths to food insecurity — NovaGovAI gives your LGU AI-powered intelligence for every dimension of community well-being.
The Philippines recorded 31,258 road crashes in 2024 — costing ₱105 billion or 4.1% of GDP. The majority are preventable with smarter road design, predictive hotspot mapping, and AI-optimized infrastructure placement.
AI analyzes PNP-HPG crash data, road geometry, lighting, and weather to predict where motorcycle crashes will happen next — and what infrastructure to build.
Maps speeding patterns by road, time-of-day, and day-of-week — recommends optimal speed bump placement, chicanes, and road narrowing.
Places signs based on approach speed, sight distance, curve radius, and glare angles — not guesswork. Generates barangay-level installation work orders.
Identifies where pedestrians are at highest risk near schools, churches, and markets — recommends raised crosswalks, bollards, and flashing beacons.
Instead of waiting for incident reports, NovaGovAI uses AI to identify where crimes are most likely to occur — and recommends lighting, patrol routes, and infrastructure to prevent them.
AI processes PNP blotter data to identify crime hotspots by type, time, and location — generating predictive heat maps updated weekly.
Cross-references crime hotspots with unlit road segments — prioritizes streetlight installation by estimated crime reduction per peso spent.
AI recommends optimal CCTV placement covering maximum high-risk zones — with cost-benefit analysis for limited LGU budgets.
Dynamic patrol routes that shift based on predicted crime windows — maximizing PNP patrol coverage with existing personnel.
NovaGovAI identifies the best locations for socialized housing, tracks ISF settlements, and ensures relocation sites have access to jobs, transport, and services.
AI scans available government land and idle lots — ranks them by proximity to jobs, transport, schools, and distance from flood/fault hazards.
Maps every informal settler concentration using satellite imagery and CBMS data — profiling each by risk exposure, population, and UDHA compliance.
Scores every potential housing site by 30-minute commute radius to employment zones — preventing "dead-end" relocations that fail families.
Auto-generates housing program applications pre-loaded with LGU's actual data — aligned with NHA, DHSUD, and RA 7279 requirements.
NovaGovAI maps classroom shortages, identifies out-of-school youth, and helps LGUs target education resources where they'll have the highest impact.
AI cross-references DepEd enrollment data with school capacity to identify which barangays need new classrooms, teachers, or school sites.
Maps schools with no internet access against DICT connectivity programs — generates DICT applications with GPS coordinates and enrollment data.
Identifies barangays with highest OSY concentration using PSA and DepEd data — recommends ALS centers, Brigada Eskwela targets, and Tulong Dunong allocation.
Auto-checks LGU education performance against SGLG indicators — generates compliance reports and flags deadlines for DepEd and DILG submission.
NovaGovAI helps LGUs optimize their Barangay Health Center network, predict disease outbreaks, and ensure PhilHealth compliance — bringing healthcare equity to the last barangay.
Identifies barangays with no BHC or RHU within 5km — scores by population, maternal mortality rate, and PHC standards compliance.
AI monitors DOH surveillance data, weather, and population density to predict dengue, leptospirosis, and respiratory illness outbreaks 2 weeks ahead.
Predicts demand for essential medicines by season and disease trend — prevents stockouts at BHCs with smart reorder scheduling.
Monitors PhilHealth membership rates by barangay — identifies uninsured household clusters and generates enrollment drive targets.
NovaGovAI maps water access gaps, monitors water district performance, and helps LGUs secure DPWH and DILG funding for waterworks projects.
Maps Level I, II, and III water access by barangay — identifies gaps against NWRB standards and WHO targets for safe water access.
AI predicts aging pipe failures using maintenance records and pressure data — prioritizes replacement by leak probability and affected population.
Alerts health officers when flood events correlate with historical waterborne disease spikes — activates water quality testing protocols.
Auto-generates SALINTUBIG and PAMANA grant applications using LGU's actual NWRB and PSA water data.
NovaGovAI identifies where jobs are and where workers aren't — optimizing zoning, TESDA placement, and economic zone planning to bring livelihoods where people live.
Cross-references PSA employment data with residential zones — identifies municipality mismatches and recommends enterprise zone rezoning.
Predicts which skills will be in demand in each LGU's economy 2 years ahead — aligns TESDA training slots with actual labor market needs.
Identifies the optimal barangays for economic zone, agri-industrial, and tourism development based on connectivity, hazard risk, and labor supply.
Monitors outcomes of DOLE and LGU livelihood programs — measures employment retention, income increase, and recommends program adjustments.
NovaGovAI monitors flood risk, waste compliance, air quality, and illegal dump sites — giving LGUs the intelligence to achieve DENR and RA 9003 compliance.
AI integrates PAGASA rainfall forecasts, watershed data, and drainage capacity to predict flood-prone zones 48 hours ahead — activates pre-emptive evacuation.
Identifies LGUs without MRF, open dump sites, and incomplete waste segregation — generates DENR compliance action plans with cost estimates.
Tracks DENR AQMS data and correlates with vehicle density, industrial zones, and wind patterns — alerts health officers when AQI exceeds safe thresholds.
Maps tree cover change using satellite imagery — supports LGU greening programs and DENR urban forest compliance reporting.
NovaGovAI monitors rice price volatility, tracks nutrition indicators by barangay, and helps LGUs optimize agricultural support — ensuring no community goes hungry.
Monitors DA and PSA rice prices in real-time — alerts LGUs when price spikes threaten food security and triggers buffer stock deployment.
Maps FNRI and OPT nutrition data by barangay — identifies clusters with critical stunting rates for targeted feeding programs and Malasakit allocation.
AI analyzes PhilAtlas soil data, rainfall patterns, and market prices to recommend the highest-value crops for each municipal agriculture zone.
Identifies post-harvest loss hotspots using DA data — recommends cold chain investments, farm-to-market road priorities, and NFA support allocation.
Every answer is grounded in real data — NAMRIA, PNP, DepEd, DILG, PAGASA. No hallucination. No guessing. Pick a question below.
Enter your LGU's operating parameters to generate a confidential, data-driven impact projection — including projected cost savings, staff efficiency gains, and grant compliance value.
Our team will demonstrate NovaGovAI using your LGU's actual data — CLUP, zoning ordinance, NAMRIA layers, and CPDO records — in a structured 30-minute technical briefing for city planners, mayors, and CPDO directors.