We process LiDAR, imagery, and multi-sensor data to build 3D models,
digital twins, and automated workflows for inspection, design, and analysis.
Our spatial AI and machine learning programs extract meaning from complex 3D and georeferenced data using sensor fusion and AI-driven spatial analysis.
These models improve accuracy and reduce manual interpretation across design, construction, and automated inspection workflows.
GDS designs and deploys industrial vision systems for manufacturing and infrastructure applications.
Our systems deliver high-speed automated inspection and analysis.
These solutions increase speed, consistency, and accuracy while minimizing rework.
We convert LiDAR and photogrammetry data into high-precision 3D geometry for modeling and simulation.
Our 3D reconstruction process creates data models that integrate directly with engineering and visualization environments, including
3D modeling and simulation platforms.
We implement AR spatial computation systems and mapping workflows that bring physical spaces into mixed-reality platforms and digital twin environments.
These tools enhance visibility and collaboration in live operational settings.
We develop visual and sensor-based positioning systems that provide precise location tracking where GPS is not available.
Each system is configured for reliability in signal-limited environments.
GDS operates focused research teams for spatial AI development, sensor fusion experiments, and algorithm testing.
These skunkwork teams accelerate product testing and reduce time to market.
We unify LiDAR, imagery, radar, and positional data within common frameworks, creating robust sensor fusion systems that provide consistent accuracy and adaptive AI capability.
At Los Angeles International Airport, GDS completed a four-million-dollar glass installation without using the project contingency budget and with only twenty-five percent of the planned manpower.
The project met every schedule and quality requirement, saving the client millions.
If you are exploring how AI, LiDAR, or spatial computation can improve performance and efficiency, schedule a 15-minute consultation with our team.
We will evaluate your objectives, identify practical opportunities, and outline a scalable plan for deployment.
Bringing the physical into the digital allows organizations to streamline operations, eliminate redundancy, and scale with confidence through
machine vision and spatial computation.
De-construct your world
Virtual asset assistance
Infrastructure and Strategy
Pioneering Digital Landscapes
Spatial Programming at GDS refers to solutions that combine machine vision, spatial data, AI and ML, and sensor fusion to connect real-world data with digital environments. It’s their advanced development capability that builds systems for automated inspection, spatial analysis, augmented reality integration, and indoor navigation — using 3D data and sensors.
GDS develops spatial machine learning models that extract meaning from complex 3D and geospatial data. This includes object recognition and classification in point clouds or imagery, anomaly detection and feature tracking over time, clustering of spatial data, and model training using LiDAR and imagery — improving accuracy and reducing manual interpretation in design, construction, and inspection workflows.
Yes. GDS designs and deploys industrial machine vision systems for manufacturing and infrastructure applications. These systems handle high-speed automated inspection tasks such as dimensional inspection, geometry validation, part recognition, and real-time defect detection on production lines — increasing inspection speed and consistency while reducing rework.
GDS converts LiDAR and photogrammetry data into high-precision 3D geometry for modeling and simulation. They handle point cloud registration and alignment, surface and mesh reconstruction from scans, feature extraction, and preparing models for CAD, BIM, or simulation environments — bridging the gap between raw scan data and usable design models.
GDS implements AR spatial computation systems and mapping workflows that bring physical spaces into mixed-reality platforms. They work on SLAM (Simultaneous Localization and Mapping), visual tracking, scene understanding, real-time data overlay for maintenance and training, and spatial simulation for digital twin environments in AR — increasing visibility and collaboration in real operational settings.
GDS creates visual and sensor-based indoor positioning and navigation systems for environments where GPS is not available. These are used for smart facilities and logistics (tracking assets or guiding people in a warehouse), personnel navigation indoors, indoor mapping, wayfinding, and location analytics for safety or efficiency.
GDS has focused research teams that engage in spatial AI development, sensor fusion experiments, and algorithm testing. They work on proof-of-concepts, prototype development, algorithm design using multi-sensor data, and workflow validation for complex systems — enabling fast deployment from experiment to production for clients who need cutting-edge custom solutions.
GDS unifies different sensor data streams — LiDAR, imagery, radar, and positional data — into common frameworks. Their sensor fusion efforts deliver higher model precision and repeatability, scalable data pipelines, and improved automation and consistency in reporting. Multiple sensors working together provide better results than any single sensor alone.
Yes. At LAX Airport, GDS completed a $4M glass installation project using spatial technology without using any of the project’s contingency budget and with only 25% of planned manpower — meeting all schedule and quality requirements and saving the client millions. This demonstrates how spatial programming can dramatically improve project efficiency and outcomes.
Key applications include: industrial vision and automated inspection systems, digital twin creation and spatial modeling, AR visualization and navigation for maintenance and training, data analytics and spatial prediction, edge spatial computation for real-time decisions, real-time monitoring for infrastructure and facilities, and R&D in spatial algorithms. Any advanced use of 3D data to automate or enhance understanding in a physical environment is a candidate for GDS’s spatial programming services.
