Geospatial Machine Learning & AI
Machine learning and AI on satellite imagery — object detection, land-cover classification, change detection and forecasting, integrated into geospatial workflows.
About this service.
We apply machine learning and deep learning to geospatial data. Using high-resolution satellite imagery, we create training data, train models, and apply them to problems such as object and feature detection and forecasting — turning imagery into automated, scalable analysis.
Beyond imagery, we integrate AI into geospatial workflows so detection, classification and prediction can run as part of your pipelines and platforms rather than as manual, one-off steps.
What we do.
How we work.
- 1
Problem definition
What to detect or predict and the success metric.
- 2
Data & labels
Prepare imagery and training labels.
- 3
Modelling
Train, validate and tune the model.
- 4
Application
Run the model over the target area or period.
- 5
Integration
Deploy into a pipeline or platform where useful.
What you get.
Where the data comes from.
Who this is for.
- Monitoring programmes needing automated detection at scale
- Environmental and carbon projects wanting model-based analysis
- Platforms that need AI built into geospatial workflows
Why Cartolytic.
- Remote-sensing and ML expertise together.
- Models trained on real high-resolution imagery.
- Built to run in production, not just in a notebook.
Frequently asked questions.
What can you detect with ML on imagery?
Objects and features in high-resolution imagery, trained to your target.
Do you build forecasting models?
Yes — predictive and forecasting models on spatial and temporal data.
Can models run automatically over time?
Yes — applied over areas/periods and integrated into pipelines.
Can you integrate AI into our existing geospatial workflow?
Yes — that's a core part of this service.
Industries using this.
Ready to start a Geospatial Machine Learning & AI project?
Let's talk about your specific needs.
We respond within 24h — based in Bucharest, active globally