Detect objects, patterns, and change faster than ever before by managing the entire geospatial ML pipeline with our cloud-native platform.
Accelerate your workflow with Picterra Forge. Build scalable machine learning models in days instead of months and unlock a new level of efficiency.
Train custom models on your own data with Picterra Forge’s intuitive tools. Cut training data needs by 99% while increasing accuracy and performance.
Run country-scale geospatial analysis in hours with fully automated model deployment. Picterra Forge handles massive datasets with ease for unmatched coverage.
Access powerful deep learning without the high costs. Picterra Forge eliminates the need for costly data science services, making advanced GeoAI affordable at scale.
With Picterra Forge you can create a scalable system to operate geospatial machine learning models in production and continuously develop them. Create deep learning models quickly and efficiently with help of smart annotation toolkit and user friendly UI. Leverage state of the art machine learning models architecture with the ability to customize the algorithms to your specific needs and benefit from best-in-class support from our team of experts.
Lead the way with powerful platform features and capabilities:
Accelerate model creation and production deployment by relying on a thoroughly tested and optimized standard detector settings. Experiment with advanced model settings such as backbone model, training tile size, or background sampling ratio.
Custom deep learning architecture optimized for geospatial imagery. Auto-scaling infrastructure with adjustable capacity to ensure predictable and efficient processing. Fast prototyping and large scale inference.
Get insights into how your model is performing, understand accuracy across multiple classes and analyze your model behavior.
Assess performance of your model. Compute accuracy score with the help of representative accuracy areas and example regions your model will run on when deployed at scale.
Intuitive model training toolbar that helps you structure all the steps required to create, train and deploy your custom model.
Easy to use web UI for no-code ML model training Import existing data using the API and advanced detector settings. Run your model on an entire image library with one click thanks to fully automated model production deployment.
Draw or upload existing detection areas. Ensure fast and accurate detectors by customizing the shape and size of detection areas. Useful when monitoring linear objects (e.g., railways, roads, rivers) or AOI scattered within the imagery.
Assign up to 10 classes in a single detector (instance & semantic segmentation). Achieve efficient and faster workflows when working with sub-classification or sub-categorization of objects within a specific class.
![his image features the Picterra "Dataset Recommendation Report" interface, a beta tool designed to improve the performance of AI detectors like the "[dataset exploration] Tree Holes" model shown in the background. The modal window explains how the tool helps users understand data variability and patterns by generating automated recommendations for training. By analyzing imagery and existing annotations, the system identifies where the detector may need more representative data to improve its generalizability.](https://picterra.ai/wp-content/uploads/2026/05/dataset-recommendation-2.webp)
