Location intelligence platform

Topic

From the PointSav Documentation

The PointSav Location Intelligence platform is a customer-owned flat-file GIS application designed for retail cluster analysis and strategic site selection — composed of app-orchestration-gis (the analytics engine) and pointsav-gis-engine (the rendering layer), with every dataset, algorithm, and rendering decision under the customer's direct control.

Updated 2026-05-08 · HistoryEspañol
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The PointSav Location Intelligence platform is a customer-owned flat-file GIS application designed for retail cluster analysis and strategic site selection — composed of app-orchestration-gis (the analytics engine) and pointsav-gis-engine (the rendering layer), with every dataset, algorithm, and rendering decision under the customer's direct control. The platform answers a fundamental commercial question — which geographic nodes possess the capital-validated density required to support adjacent development? — by transforming raw store locations into actionable commercial nodes through the co-location-methodology. All canonical datasets reside in a Totebox Archive as flat JSONL and GeoParquet files, applying the WORM ledger discipline to geospatial records.

[edit]Operational Capabilities

The platform transforms raw store locations into actionable commercial nodes by executing the Retail Co-location Methodology. It answers a fundamental commercial question: which geographic nodes possess the capital-validated density required to support adjacent development?

[edit]1. Five-Degree Cluster Identification

The platform computes co-location clusters around Primary Target anchors (e.g., Walmart Supercentres) using a deterministic spatial algorithm. Each cluster is scored based on the convergence of independent, capital-intensive operators (Costco, Home Depot, etc.) and supporting civic infrastructure (hospitals, universities).

[edit]2. Multi-Layer Interactive Interface

The interactive map at gis.woodfinegroup.com uses a three-layer architecture:

  • Layer 1 — Global POIs: Toggled view of 31,000+ individual retail locations, color-coded by brand family.
  • Layer 2 — Co-location Clusters: The primary analytical view, encoding cluster strength through visual saturation and size.
  • Layer 3 — Catchment Radii: Visualized proximity boundaries (default 3.0 km) that define the scope for trade-area analysis and mobility data procurement.

[edit]Sovereign Architecture

The platform adheres to the pointsav-gis-engine principles of customer-rooted data sovereignty:

  • Flat-File Operation: All data persists as versioned JSONL and GeoParquet files within a Totebox Archive, rather than a running database daemon.
  • Open Standards Rendering: Uses PMTiles and MapLibre GL JS to serve vector maps directly from standard web servers, eliminating proprietary tile-API dependencies.
  • Reproducible Build: If a gateway node is destroyed, the application surface can be re-provisioned instantly by pointing a fresh instance at the immutable data layer.

[edit]Data Foundations and Licensing

The platform integrates high-fidelity open data sources to ensure transparency and auditability:

  • Retail Data: Sourced from OpenStreetMap contributors and the Overture Maps Foundation.
  • Civic Infrastructure: Healthcare and institutional records from the Overture Maps Foundation Places dataset.
  • Sovereign Basemap: OpenFreeMap liberty tiles served via the PointSav infrastructure.

Material assumptions for current platform performance include the continued availability of high-fidelity open geographic datasets. [osm-odbl] [overture-maps-cdla-2-0]

[edit]Future Roadmap

Planned enhancements to the platform surface include the integration of origin-destination (OD) mobility data for trade-area flow analysis and the expansion of the European institutional dataset. [ni-51-102] [osc-sn-51-721]

[edit]See also

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