What do you like best about the product?

We have been working with GridGain for about a year to help us continuously train our AI and ML models. Their Continuous Learning Framework supports machine learning and deep learning model training on operational data, with built-in machine learning libraries that facilitate training models using real-time data. GridGain also provides us with high-speed data processing and analytics, and near-linear scalability which have been key to helping us handle large datasets and perform the complex computations required in AI and ML training.

What do you dislike about the product?

We’ve experienced minor issues with some of our data integrations when it came to scaling our AI and ML models.

What problems is the product solving and how is that benefiting you?

GridGain helps us train and deploy our AI and ML models without costly infrastructure or complex configurations. The in-memory computing delivers high-speed processing at scale which has been key to our handling massive datasets and performing the complex computations we need in AI and ML training. Additionally, GridGain supports near real-time continuous learning against massive amounts of data, eliminating the need for data movement.