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| schema: foundry-doc-v1 | schema: foundry-doc-v1 |
| title: "PointSav GIS engine" | title: "PointSav GIS engine" |
| slug: pointsav-gis-engine | slug: pointsav-gis-engine |
| category: services | category: services |
| type: topic | type: topic |
| content_type: topic | content_type: topic |
| quality: complete | quality: complete |
| 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 |
| short_description: "The PointSav GIS Engine is a customer-owned location intelligence platform built in Rust for offline-first, flat-file operation — a structural departure from geographic information systems that rely on centralised database instances and continuous network connectivity." | short_description: "The PointSav GIS Engine is a customer-owned location intelligence platform built in Rust for offline-first, flat-file operation — a structural departure from geographic information systems that rely on centralised database instances and continuous network connectivity." |
| paired_with: pointsav-gis-engine.es.md | paired_with: pointsav-gis-engine.es.md |
| cites: | cites: |
| - maplibre-gl-js | - maplibre-gl-js |
| - pmtiles-spec | - pmtiles-spec |
| - tippecanoe-tool | - tippecanoe-tool |
| --- | --- |
| A location-intelligence platform that depends on a central database and a live network is a platform a customer rents, not owns — outages, per-seat cloud cost, and air-gap ineligibility follow. The PointSav GIS Engine runs offline-first from flat files: it reads from a static PMTiles archive on the customer's own [[service-fs-data-lake|filesystem]], renders interactively through MapLibre GL JS in the browser, and serves every query without an external dependency. For a regulated buyer, the spatial record is auditable, portable, and never leaves the building. | A location-intelligence platform that depends on a central database and a live network is a platform a customer rents, not owns — outages, per-seat cloud cost, and air-gap ineligibility follow. The PointSav GIS Engine runs offline-first from flat files: it reads from a static PMTiles archive on the customer's own [[service-fs-data-lake|filesystem]], renders interactively through MapLibre GL JS in the browser, and serves every query without an external dependency. For a regulated buyer, the spatial record is auditable, portable, and never leaves the building. |
| ## Architectural Principles | ## Architectural Principles |
| The engine operates as a stateless application surface, decoupling the data layer from the runtime so either can be updated or replaced independently. | The engine operates as a stateless application surface, decoupling the data layer from the runtime so either can be updated or replaced independently. |
| ### Flat-File Substrate | ### Flat-File Substrate |
| Unlike centralised GIS stacks that require persistent database management, the PointSav engine uses a flat-file substrate. It consumes geographic data directly from `JSONL`, `GeoParquet`, and `YAML` formats versioned within a Totebox Archive. This architecture ensures the data layer remains entirely decoupled from the application logic, eliminating database maintenance overhead and preventing vendor lock-in. | Unlike centralised GIS stacks that require persistent database management, the PointSav engine uses a flat-file substrate. It consumes geographic data directly from `JSONL`, `GeoParquet`, and `YAML` formats versioned within a Totebox Archive. This architecture ensures the data layer remains entirely decoupled from the application logic, eliminating database maintenance overhead and preventing vendor lock-in. |
| ### Sovereign Rendering Stack | ### Sovereign Rendering Stack |
| The platform avoids commercial SaaS mapping dependencies by using an open-source rendering stack: | The platform avoids commercial SaaS mapping dependencies by using an open-source rendering stack: |
| - **PMTiles:** A single-file archive format for tiled data that enables maps to be served directly from standard web servers (Nginx) or blob storage without a dedicated tile server. [pmtiles-spec] | - **PMTiles:** A single-file archive format for tiled data that enables maps to be served directly from standard web servers (Nginx) or blob storage without a dedicated tile server. [pmtiles-spec] |
| - **MapLibre GL JS:** A WebGL-based library for rendering interactive vector maps in the browser. [maplibre-gl-js] | - **MapLibre GL JS:** A WebGL-based library for rendering interactive vector maps in the browser. [maplibre-gl-js] |
| - **Tippecanoe:** A tool used to compile massive flat-file datasets into optimized vector tiles, ensuring rapid delivery of complex co-location clusters. [tippecanoe-tool] | - **Tippecanoe:** A tool used to compile massive flat-file datasets into optimized vector tiles, ensuring rapid delivery of complex co-location clusters. [tippecanoe-tool] |
| ## Spatial Processing and Orchestration | ## Spatial Processing and Orchestration |
| The engine's core logic resides in the [[app-orchestration-gis]] service. This component executes the [[co-location-methodology|Woodfine co-location methodology]] deterministically: | The engine's core logic resides in the [[app-orchestration-gis]] service. This component executes the [[co-location-methodology|Woodfine co-location methodology]] deterministically: |
| 1. **Ingestion:** Reads retail and civic infrastructure records from the [[totebox-os|Totebox]] Archive via [[service-business-clustering]] and [[service-places-filtering]]. | 1. **Ingestion:** Reads retail and civic infrastructure records from the [[totebox-os|Totebox]] Archive via [[service-business-clustering]] and [[service-places-filtering]]. |
| 2. **Analysis:** Executes spatial joins and proximity queries to identify co-location clusters across 1.0 km, 3.0 km, and 5.0 km radii. | 2. **Analysis:** Executes spatial joins and proximity queries to identify co-location clusters across 1.0 km, 3.0 km, and 5.0 km radii. |
| 3. **Ranking:** Applies the 12-rank named-anchor matrix to generate site quality tiers. | 3. **Ranking:** Applies the 12-rank named-anchor matrix to generate site quality tiers. |
| 4. **Serialization:** Outputs the processed results as tiled data for the visual interface at [gis.woodfinegroup.com](https://gis.woodfinegroup.com). | 4. **Serialization:** Outputs the processed results as tiled data for the visual interface at [gis.woodfinegroup.com](https://gis.woodfinegroup.com). |
| This stateless approach ensures that the entire GIS environment can be re-provisioned instantly from the immutable data layer, providing maximum service resilience and auditability. | This stateless approach ensures that the entire GIS environment can be re-provisioned instantly from the immutable data layer, providing maximum service resilience and auditability. |
| ## See also | ## See also |
| - [[co-location-methodology]] — the ranking methodology that drives tier assignment in the GIS engine | - [[co-location-methodology]] — the ranking methodology that drives tier assignment in the GIS engine |
| - [[app-orchestration-gis]] — the orchestration layer that runs the spatial analysis pipeline | - [[app-orchestration-gis]] — the orchestration layer that runs the spatial analysis pipeline |
| - [[service-business-clustering]] — retail clustering service feeding the GIS tier computation | - [[service-business-clustering]] — retail clustering service feeding the GIS tier computation |
| - [[service-places-filtering]] — civic infrastructure filtering service feeding the GIS tier computation | - [[service-places-filtering]] — civic infrastructure filtering service feeding the GIS tier computation |
| - [[service-fs-data-lake]] — the flat-file data lake that backs all GIS source data | - [[service-fs-data-lake]] — the flat-file data lake that backs all GIS source data |
| - [[gis-as-bim-substrate|GIS as BIM Substrate]] — how the GIS engine functions as a BIM data layer | - [[gis-as-bim-substrate|GIS as BIM Substrate]] — how the GIS engine functions as a BIM data layer |
| - [[build-a-colocation-map]] — step-by-step guide: run a co-location cluster analysis and render the results on a map | - [[build-a-colocation-map]] — step-by-step guide: run a co-location cluster analysis and render the results on a map |
| ## References | ## References |
| - [Geographic information system](https://en.wikipedia.org/wiki/Geographic_information_system) — Wikipedia, accessed 2026-06-14 | - [Geographic information system](https://en.wikipedia.org/wiki/Geographic_information_system) — Wikipedia, accessed 2026-06-14 |