manot boosts your models performance by effectively detecting outliers and proposing good data.
manot allows companies that use Computer Vision systems to monitor the performance of their models in the real world. We reduce the feedback time from months to hours, filter out huge datasets to propose new samples of data for your training data set, improve the accuracy of your model and reduce costs by 50%.
manot's data proposal system suggests samples of data to add to your training dataset to improve the accuracy of your model.
Monitor the performance of your computer vision models in the production environment to see how they are operating.
Identify out-of-distribution data samples as they happen and gain insights on why your model is failing.