manot boosts your model 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%.
The model detects the moon incorrectly as a traffic light, potentially causing an accident.
Identify outliers such as natural objects like the moon, correctly label them and reduce accidents.
manot's data proposal system 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 it is operating.
Identify out-of-distribution data samples as they happen and gain insights on why your model is failing.