Intelligent Geospatial Analytics with AI/ML
Our AI/ML integration services transform traditional GIS into intelligent spatial decision systems. We develop custom machine learning models that extract insights from geospatial data at scale, enabling predictive analytics and automated feature detection for smarter governance.
Deep Learning Models
CNN, RNN, and Transformer architectures for spatial dataRemote Sensing AI
Automated analysis of satellite/aerial imageryCapabilities
Automated Feature Extraction
Building footprints, road networks, land use classification from imagery
Change Detection
Identify construction, deforestation, urban expansion over time
Predictive Modeling
Flood risk, urban growth, infrastructure demand forecasting
Anomaly Detection
Identify unauthorized constructions, encroachments, or irregularities
Our AI/ML Workflow
Use Case Identification
Collaboratively define the spatial intelligence challenge and success metrics
Geospatial Training Data
Curate and label datasets, perform augmentation for robust model training
Algorithm Selection & Training
Develop custom models using TensorFlow, PyTorch, or specialized libraries like Raster Vision
Accuracy Assessment
Quantify performance using spatial accuracy metrics and ground truth verification
Production Integration
Implement models within your existing GIS workflows via APIs or custom applications
Technical Specifications
AI/ML Techniques
- Computer Vision (CV)
- Deep Learning
- Geospatial Tensor Analysis
- Time Series Forecasting
Data Types Processed
- Satellite/Aerial Imagery
- LiDAR Point Clouds
- IoT Sensor Feeds
- 3D City Models
Implementation Options
- Cloud-based AI Services
- On-premise Deployment
- Hybrid Edge Computing
Accuracy Benchmarks
Our models consistently achieve 85-95% accuracy depending on data quality and problem complexity
AI Readiness Assessment
Evaluate your organization's potential for geospatial AI adoption.
Get Free Evaluation