To train secure computer vision models, you need secure datasets. Quickly uncover weaknesses in your data and automate an array of advanced corrections to keep your models one step ahead.

Dataset Relevance

Training datasets and production datasets are often mismatched. Our algorithms analyze both datasets to determine where training data are missing. New datasets are built using a combination of training, production, and synthetic data, ensuring that your data (and models) stay relevant.

Model Security from
Data Security.

We close the gaps in your datasets by staying on the cutting edge of computer vision and machine learning. Using our technology we find and mitigate risks and vulnerabilities in your data, allowing you to train secure models.

Dataset Correction

Data labeling services often leave errors behind. We use data embeddings to find and correct errors in data categorizations. These corrections save hours of manual work and improve the performance of data applications.



Mynah.reiform Demo Out Now!

Posted 02/11/23 by Ben Parfitt

Reiform© Mynah, our fully featured set of tools for computer vision data preparation is accompanied by a user interface that walks you through the process of analyzing, visualizing, and cleaning data while giving you control of your data. Mynah is currently in a closed alpha. Feel free to reach out if you are interested in trying out the platform!

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