Expedite and simplify data labeling.
Intel® Geti™ Software
Build computer vision models in a fraction of the time and with less data.
Intel® Geti™ software eases laborious data upload, labeling, model training, retraining, and optimization tasks across the computer vision model development process. Now, teams can quickly build vision models for a wide range of processes, including detecting defective parts in a production line, reducing downtime on the factory floor, automating inventory management, or other automation projects.
Enhancing AI from Data Labeling to Model Training and Export
Build effective models with less data.
Simplify and automate the development pipeline.
Combine multiple computer vision tasks to solve complex problems.
Output production-ready models for the OpenVINO™ toolkit.
Build AI models at scale with Intel Geti software and the Open Edge Platform.
Develop New Computer Vision AI Models in Days
Explore core capabilities behind the next-generation computer vision AI software.
Interactive Model Training
Get started annotating data with as few as 20 to 30 images, and then let active learning help you teach the model as it learns.
Multiple Computer Vision Tasks
Create models for AI tasks, including classification, object detection, semantic segmentation, and anomaly detection.
Task Chaining
Train your model into a multistep smart application by chaining two or more tasks without the need to write additional code.
Smart Annotations
Expedite data annotation and easily segment images with professional drawing features like a pencil, a polygon tool, OpenCV GrabCut, and AI models such as the Segment Anything Model.
Production-Ready Models
Output deep learning models in TensorFlow* or PyTorch* formats (where available) or as an optimized model for the OpenVINO™ toolkit to run on Intel® architecture CPUs, GPUs, and VPUs.
Hyperparameter Optimization
Refining hyperparameters is critical to the model’s learning process. Built-in optimization makes a data scientist’s job easier.
Rotated Object Detection
Support for rotated bounding boxes extends the training simplicity and accuracy to datasets with images that are not axis-aligned.
Model Evaluation
Comprehensive statistics to assess your model’s performance.
Enabling Collaboration that Adds Value
Cross-functional AI teams collaborate in a single UI to analyze results in real time. The graphical interface allows team members with little or no AI experience to help train computer vision models. Enabling functionalities such as annotation assistants, drawing features, and object detection assistants make model training drag-and-drop simple.