Densify, a company that helps enterprises make sure that they’re using their compute resources to the fullest extent possible, announced a new service today that uses AI to cut down customers’ cloud bills. The Cloud Learning Optimization Engine (Cloe for short) analyzes workloads using machine learning to determine how much CPU, RAM, and storage they need, then suggests ways to save money.

Cloe has helped customers like Bank of America, Honda, and IBM save an average of 40 percent on their cloud bills, with some customers seeing savings of more than 80 percent. After analyzing the needs of each workload, it suggests compute instances companies can shut down, workloads that can sit on the same instance to save money, and ways to optimize which types of virtual machines customers use in order to reduce their spend.

As more companies move their workloads to the public cloud, the sort of optimization work that Cloe helps with is an important component of ensuring that businesses aren’t spending too much on their computing infrastructure. Densify CEO Gerry Smith said that the company’s product was aimed at solving the core problem in infrastructure optimization: Customers don’t know what resources their applications actually need to perform well. That can be costly when they’re paying by the hour for compute capacity their applications will never use.

The service works across Amazon Web Services, Microsoft Azure, Google Cloud Platform, and IBM’s cloud offerings, so customers can see which environments can handle their workloads most efficiently. Cloe has a normalized understanding of each…

[SOURCE]