Recent posts by Mona

In today's data-driven world, organizations increasingly rely on data to inform their decision-making, resulting in the need for efficient and accurate data analysis tools. In the last two decades, a plethora of tools for analytics, data science, and BI have been created to meet this need. However, one basic problem in data analysis has remained elusive: the problem of automating multivariate exploratory analysis clearly and free of noise.

We recently announced our latest innovation to our intelligent monitoring platform - Mona’s new AI fairness feature. This feature assists with eliminating bias with AI-driven applications, increasing trust in your machine learning models in production to ensure compliance readiness.

In recent years, the topic of AI democratization has gained a lot of attention. But what does it really mean, and why is it important? And most importantly, how can we make sure that the democratization of AI is safe and responsible? In this blog post, we'll explore the concept of AI democratization, how it has evolved, and why it's crucial to closely monitor and manage its use to ensure that it is safe and responsible.

Monitoring is crucial to ensuring that ML models deployed in production are serving their intended purpose and operating as expected, but how soon is too soon to implement a monitoring solution? Ultimately it depends on the extent to which the models are integrated into business processes, and this blog post will walk through the considerations that should be made before deciding to implement an ML monitoring solution.