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| schema: foundry-doc-v1 | schema: foundry-doc-v1 |
| title: "Location intelligence platform" | title: "Location intelligence platform" |
| slug: location-intelligence-platform | slug: location-intelligence-platform |
| category: applications | category: applications |
| type: topic | type: topic |
| quality: complete | quality: complete |
| short_description: "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." | short_description: "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." |
| status: active | status: active |
| audience: public | audience: public |
| bcsc_class: public-disclosure-safe | bcsc_class: public-disclosure-safe |
| language_protocol: PROSE-TOPIC | language_protocol: PROSE-TOPIC |
| last_edited: 2026-05-08 | last_edited: 2026-05-08 |
| editor: pointsav-engineering | editor: pointsav-engineering |
| paired_with: location-intelligence-platform.es.md | paired_with: location-intelligence-platform.es.md |
| cites: | cites: |
| - osm-odbl | - osm-odbl |
| - overture-maps-cdla-2-0 | - overture-maps-cdla-2-0 |
| - ni-51-102 | - ni-51-102 |
| - osc-sn-51-721 | - osc-sn-51-721 |
| --- | --- |
| 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]]. | 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]]. |
| ## Operational Capabilities | ## Operational Capabilities |
| The platform transforms raw store locations into actionable commercial nodes by executing the [Retail Co-location Methodology](co-location-methodology). It answers a fundamental commercial question: *which geographic nodes possess the capital-validated density required to support adjacent development?* | The platform transforms raw store locations into actionable commercial nodes by executing the [Retail Co-location Methodology](co-location-methodology). It answers a fundamental commercial question: *which geographic nodes possess the capital-validated density required to support adjacent development?* |
| ### 1. Five-Degree Cluster Identification | ### 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). | 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). |
| ### 2. Multi-Layer Interactive Interface | ### 2. Multi-Layer Interactive Interface |
| The interactive map at [gis.woodfinegroup.com](https://gis.woodfinegroup.com) uses a three-layer architecture: | The interactive map at [gis.woodfinegroup.com](https://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 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 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. | - **Layer 3 — Catchment Radii:** Visualized proximity boundaries (default 3.0 km) that define the scope for trade-area analysis and mobility data procurement. |
| ## Sovereign Architecture | ## Sovereign Architecture |
| The platform adheres to the [PointSav GIS Engine](pointsav-gis-engine) principles of data sovereignty: | The platform adheres to the [PointSav GIS Engine](pointsav-gis-engine) principles of data sovereignty: |
| - **Flat-File Operation:** All data persists as versioned JSONL and GeoParquet files within a Totebox Archive, rather than a running database daemon. | - **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. | - **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. | - **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. |
| ## Data Foundations and Licensing | ## Data Foundations and Licensing |
| The platform integrates high-fidelity open data sources to ensure transparency and auditability: | The platform integrates high-fidelity open data sources to ensure transparency and auditability: |
| - **Retail Data:** Sourced from OpenStreetMap contributors and the Overture Maps Foundation. | - **Retail Data:** Sourced from OpenStreetMap contributors and the Overture Maps Foundation. |
| - **Civic Infrastructure:** Healthcare and institutional records from the Overture Maps Foundation Places dataset. | - **Civic Infrastructure:** Healthcare and institutional records from the Overture Maps Foundation Places dataset. |
| - **Sovereign Basemap:** OpenFreeMap liberty tiles served via the PointSav infrastructure. | - **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]* | *Material assumptions for current platform performance include the continued availability of high-fidelity open geographic datasets. [osm-odbl] [overture-maps-cdla-2-0]* |
| ## Future Roadmap | ## 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] | 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] |