Teaching a Computer to See is a Complex and Painstaking Task
Computer vision algorithms need extraordinary volumes of labeled data to make sense of the visual world. The speed and accuracy with which your system learns to navigate the world are directly correlated to the quality of your training data. By improving data labeling accuracy through small batch testing and continuous iteration, Alegion enables customers to develop high performing CV models and greater opportunities for feature and product differentiation.
Computer Vision Capabilities
Our platform supports project-specific tool and task configurations to optimize labeling accuracy and throughput for image and video data points.
Leverage Our Data Labeling Expertise
Train your CV model with large-scale, custom-labeled datasets without the burden of building or acquiring labeling tools, finding and curating a qualified workforce, or managing a large-scale data annotation project. Shorten your time to ROI and mitigate the risks of sub-par model performance with high quality data, annotated and validated by a combination of task-trained human annotators and ML-enhanced tools.

Accelerate projects with Human and AI
Make decisions more quickly and with more confidence by relying on our platform to integrate the best of human and machine intelligence. Higher accuracy and fewer cycles mean a faster time to value for ML initiatives.
