Cwlwm Systems
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Case study 04

Location Intelligence & Geospatial Data Platform

A repeatable geospatial pipeline that turns service, delivery, territory, ownership, or operating boundaries into normalized location-level records that downstream teams can actually use.

Applicable to
UtilitiesLogisticsReal estateTerritory planningFranchise expansionInfrastructure operations
01

Before

Businesses often define an operating area with geographic shapes while sales and operations need specific addresses, properties, assets, or locations.

Large reference datasets make brute-force spatial matching slow and expensive.

Automated processing needs lineage, repeat-upload protection, locks, and safe recovery.

02

The system

The pipeline parses and repairs geometry, reduces the candidate universe before exact spatial evaluation, normalizes and deduplicates matched records, and preserves processing lineage for repeatable downstream use.

01Ingest boundary→
02Repair→
03Filter→
04Spatial match→
05Normalize→
06Export→
07Reuse
03

Capabilities

Geometry parsing and repair
Coordinate transformation
Candidate-set reduction
Exact point-in-polygon matching
Record normalization
Deduplication
Processing locks and recovery
Lineage tracking
04

Operational outcome

1

Translate map boundaries into specific operational records.

2

Reduce unnecessary spatial processing before expensive exact matching.

3

Create repeatable datasets instead of one-off GIS exports.

4

Protect automated processing from duplicate or stale jobs.

Case studies are presented as representative system patterns. Client-specific names, screenshots, testimonials, and measured results are only published with permission.

05

Technical foundation

The technology is selected to support the operating model, not the other way around. A system of this type may combine the following foundations:

Python data pipelineSpatial SQLGeometry librariesCloud processingColumnar query engineLineage controls

Could this pattern fit your business?

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The case study shows a reusable operating pattern, not a boxed product. I can adapt the architecture to the people, data, systems, and rules already inside your business.

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Technology experience

Tools I use to build.

Languages, frameworks, databases, cloud platforms, and development tools I use to design and build business systems.

Next.js
React
TypeScript
JavaScript
Python
HTML5
CSS
PostgreSQL
Supabase
Google Cloud
BigQuery
GitHub
Vercel
WordPress
Security & data practices

The stack matters. How it is configured matters more.

Business systems can contain sensitive operational and customer information. I design around practical controls such as least-privilege access, secure credential handling, authorization boundaries, environment separation, logging, and recovery planning appropriate to the project.

Read Security Practices →
01

Least-privilege access

Users and services are given only the access their role or workflow requires.

02

Secure credentials

API keys, service credentials, and environment secrets are kept out of public source and client-side code.

03

Protected data flows

Encrypted connections and appropriate authorization controls are used for production data paths where supported.

04

Environment separation

Development, staging, and production concerns are separated when the project risk and scope call for it.

05

Validation & auditability

Business rules, permissions, input boundaries, logging, and failure handling are treated as part of the system design.

06

Recovery planning

Backup, retention, and recovery responsibilities are defined according to the system and the agreed scope.

Security controls are scoped to the needs of each engagement. Formal compliance or certification requirements should be identified during discovery and documented in the applicable statement of work.