Cathy O'Neil says, 'Synthetic data is likely to get better over time, but not by accident.' We couldn't agree more, and our world-class team of scientists and engineers is constantly working on just that.

MOSTLY AI has gathered a team of exquisite experts and data science enthusiasts. We would like you to meet our team 'eye to eye' and get to know all our devoted Mostlies who ensure that we deliver the best product and stand out in the market.

Any machine learning model that is trained on fair synthetic data will be representative of the real world but fair by design.

MOSTLY GENERATE now ships with geo data support, thus allowing any organization to synthesize and truly anonymize their geo enriched data assets at scale. In this blogpost we present examples of synthetic geo data using publicly available datasets.

In the following blog post, I'll give an overview of the most common data and privacy business problems I hear about from our clients.

Watch the 6th Synthetic Data Meetup on-demand where we have hosted an expert in residential energy systems who had a fascinating story to tell!

Our developers worked hard to deliver much anticipated new features to simplify our customers' lives with faster, safer, and easier processes.

Working with SOC 2 certified vendors, such as MOSTLY AI, assures the customers that the vendor follows consistent security practices and are able to keep customers’ valuable data always safe and protected through the implementation of standardized controls as defined in the AICPA Trust Service Principles framework.

Having an environmentally responsible business in 2021 leads to healthy, productive, and forward-thinking employees without jeopardizing growth and profitability. Companies like ours are the future, and we believe that by implementing environmentally conscious efforts early on, we can create long-term sustainability.

AI governance requires access to models just as well as to data. However, sensitive training data cannot be shared further. MOSTLY AI’s highly representative synthetic data serves as a drop-in replacement to enable model documentation, model validation, as well as model certification.