Spatial Data Services
A structured approach to capturing, digitizing, validating, and maintaining network data across Telecom, Fiber, Utilities, and Cadastral systems.
12thWonder delivers enterprise-grade spatial data services that support accurate capture, digitization, validation, and maintenance of network data. Our approach is designed for precision, scalability, and long-term data integrity, enabling organizations to manage complex network assets reliably across office, cloud, and field environments.
Capabilities Designed for Enterprise Network Conversion
What we Core Capabilities for Large-Scale Network Digitization deliver
NetGraph
Efficient network digitization
Configurable rule-based validations
Domain- rich and extensible data models
Multiuser workflows with data integrity
Seamless data exchange & integration
Scalable and future-ready design
Smart digitization experience
Network Improvements & Maintenance
Maintain data accuracy as networks evolve through controlled, rule-based validation.
Real-time validation during incremental updates
Automatic dependency checks across network elements
Reduced errors during maintenance and expansion
Consistent data integrity over time
Minimize network failures. Extend asset life.
Data Conflations & Positional Accuracy Improvements
Keep network data aligned with ground reality
Minimal control points
Automatic geometry adjustment
Confidence scoring for faster review
Reduced false positives
Accurate, up-to-date network positioning with less manual effort.
Impact at Scale
Measured performance across large GIS programs
faster GIS digitization
spatial data accuracy
Incremental consistency
reduction in operator effort
fewer field reworks
Resource Center
Insights, case studies, and guides to help you maximize your geospatial investments.
Why Field Operations Break When You Can’t See Them on a Map
Field operations rarely fail because teams are not working hard enough. They fail when leaders lose visibility into what is happening, where it is happening, and why.
Building Smarter Cities: Reduced Maintenance Costs by 40% with Digital Twins & 3D GIS
A leading urban utility company in the U.S. faced rising maintenance costs, frequent service disruptions
What Your GIS Data Actually Needs for GeoAI
We examined why many GeoAI projects fail before they even get started in the previous blog. Let's now discuss what makes GeoAI function in the real world.
Ready to clean up your spatial data once and for all?
Fix messy GIS data without slowing projects down.
