Running applications in the cloud is complex and expensive. As legacy applications are modernised and migrated to the cloud, and new use cases emerge —like companies that have started running and training AI models that demand specialised GPUs and require billions of computations per second and petabytes of data costs rise.
For enterprises training and running their own large language models, the resulting cloud bill can cost as much as $700,000 a day, as is the case for OpenAI’s infrastructure cost on Azure.
CAST AI’s platform goes beyond monitoring clusters and making recommendations; it utilises advanced machine learning algorithms and heuristics to analyse and automatically optimise clusters.
This saves customers 50 percent or more on their cloud spend, improving performance and reliability and boosting DevOps and engineering productivity.
The funding is raised from Vintage Investment Partners and existing investors Creandum, and Uncorrelated Ventures, and follows a $20 million investment round led by Creandum in March, bringing the company’s total funding raised to $73 million.
Vintage Investment Partners’ Barrel Kfir shared:
“What is unique about CAST AI is that it has developed a robust platform that goes beyond monitoring and recommendations; it automatically optimises customers’ cloud resources, supercharging their savings.”
According to CAST AI co-founder and CEO Yuri Frayman:
“The new funding will further bolster customer savings and productivity as we expand our platform’s capabilities and automate even more aspects of Kubernetes.”
Lead image via CAST AI.