Variable Universe
Structured indicators across official statistics, fiscal records, land systems, facilities, places, and satellite-derived activity signals.
Spatial Economic Model
AI spatial economy system for cities, regions, and investment decisions
A geospatial econometric platform that connects official economic data, municipal finance, administrative records, satellite signals, land systems, places data, and client datasets into one operational model of the economy.
Platform
One model fabric for the real spatial economy
The Spatial Economic Model links economic performance, settlement growth, firm activity, land use, infrastructure access, municipal finance, trade, property, service pressure, and night-light intensity into a shared spatial evidence layer.
Econometric Models
Nowcasting, accessibility, resilience, fiscal health, investment opportunity, inequality, and spatial growth models.
Decision Surfaces
Comparable spatial outputs for prioritisation, scenario testing, corridor planning, investment cases, and local economic strategy.
Dataset universe
A national-scale data spine, extensible to client systems
The model is designed around data families rather than one-off indicators, so each client engagement can extend the same evidence base with local administrative records, project pipelines, facilities, parcels, and proprietary datasets.
SARB
Macro, financial, price, credit, and national accounts context for economic conditions and cycle sensitivity.
Stats SA
Census, community survey, labour, demographic, household, price, enterprise, and official statistical series.
SEADsa
Firm, employment, sector, and local economic activity signals used to understand business geography and momentum.
Treasury / MFMA
Municipal financial performance, budgets, spending, revenue, grants, and fiscal health indicators.
DTIC + Departments
Industrial policy, investment, trade, incentives, infrastructure, and sector programme data from national departments.
Provincial + Municipal
Administrative records, local registers, permitting, service delivery, assets, facilities, and project pipelines.
GHSL + Land Cover
Built-up change, population grids, urban expansion, settlement form, land transformation, and land-use classification.
VIIRS
Night-light intensity, growth, decline, anomaly, and activity proxies for high-frequency spatial economic monitoring.
Google Places + Client Data
Business locations, amenities, points of interest, customer data, operations data, and client-owned spatial layers.
Model intelligence
From raw layers to explainable spatial recommendations
The platform turns the variable universe into model-ready surfaces: harmonised geographies, comparable time series, source lineage, feature engineering, spatial joins, forecast-ready panels, and explainable outputs for planners, economists, investment teams, and executives.
Ingest and govern
Connect official, administrative, satellite, places, and client datasets into governed spatial tables.
Harmonise geography
Align sources across metros, districts, municipalities, wards, hexes, corridors, parcels, and catchments.
Model outcomes
Estimate activity, accessibility, sector resilience, property dynamics, fiscal pressure, and investment readiness.
Decide with evidence
Generate ranked opportunity surfaces, scenario comparisons, evidence packs, and board-ready spatial narratives.
Multi-metro proof
A reusable model fabric across South African metros
Cape Town leads this local design direction, with the same VIIRS-driven visual and analytical language extending across Johannesburg, Tshwane, and Ekurhuleni.
Cape Town
Johannesburg
Tshwane
