NexSight is an industrial AI vision platform powered by advanced deep learning technology. It leverages Aqrose's proprietary computer vision library as its core, offering a comprehensive range of services, including image annotation, model building, and project deployment. It is designed to cater to diverse visual inspection scenarios in the industrial field.


Image upload
Online labeling
Model building
Model verification
Model export
Deployment and launch

Product Strength

Outstanding performance for versatile scenarios

Effectively responds to dection difficulties, such as low contrast, multiple types, complicated backgrounds, and small defect scales. Adapts to high-speed production lines and supports tiny sample projects.

Multi-function and efficient deployment

Enable building high-quality models and improving deployment efficiency with comprehensive acceleration of 65% to 90%.

Flexible secondary development and cost saving

Provides standardized interfaces and flexible programming language choices; Detects multiple defect types and gives comprehensive result for single image; No secondary development needs and time and labor saving.

Unlimited computer ends, economic integration

Cloud-based training service, images, and models stored in the cloud, accessible from any network computer.



Performs pixel-level detection, accurately recognize location, size, and category of minor defects on the surface of products in complicated situations/projects.



Classifies entire images, suitable for grading and sorting agricultural products, classifying industrial defects, etc.



Performs region-level detection on images, accurately recognizing multiple classes of objects or defects.


Unsupervised segmentation

Performs pixel-level detection on all known and unknown defects with just a reference image of a defect-free product for rapid deployment and verification. Advantages in addressing detection scenarios on high-yield production lines, effectively tackling challenges such as limited time for defect sample collection.


Unsupervised classification

Performs whole-image classification on all known and unknown defects with just a reference image of a defect-free product for rapid deployment and verification. Often used to detect unpredictable category anomalies on production lines.



Excels in precise positioning and efficient recognition of characters in images with overlapping, distorted, skewed, and complicated backgrounds.


Application scenarios

Defect detection

Defect categorization

Categorization and classification