At the same time, CV models tend to be significantly more failure-prone than other modalities because images are very high-dimensional, necessitating models that are more complex and less interpretable. Furthermore, the data itself is harder to understand and classify. Robust Intelligence helps you eliminate CV model failure.
Ensure that your models perform well across all types of data. Explicitly check for invariance to data transformations, robustness to noise and attacks, and generalizability across meaningful image features.
Automatically identify problematic data points as data streams in during production. Seamlessly augment the model retraining and redeployment process. Take action against bad inputs so they never reach your model.
Overcome notoriously difficult CV monitoring challenges by also tracking semantically relevant features of image data. Continuously monitor models in production to identify issues, understand when it’s time to retrain a model, and automate root cause analysis of model failure.
Evaluate any image classification or object detection model. Robust Intelligence configures tests based on your setup to serve insights relevant to your use case. More use cases are always on the way.
Test any type of model (statistical, convolutional neural net, transformer, etc.) and pull data from any source (local, networked, cloud) using our simple and flexible abstractions.
Use metadata attributes to test model and data performance in context and catch when your model is underperforming. Robust Intelligence allows users to provide their own custom metadata.