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VESSL AI secures $12M for its MLOps platform that aims to cut GPU costs by up to 80%
South Korean MLOps platform VESSL AI is trying to carve out a niche for itself by focusing on optimizing for GPU expenses using hybrid infrastructure.
As businesses increasingly integrate artificial intelligence in their workflows and products, there is a growing demand for tools and platforms that make it easier to create, test and deploy machine learning models. This category of platforms — popularly known as machine learning operations, MLOps — is already a little crowded, with startups like InfuseAI, Comet, Arrikto, Arize, Galileo, Tecton and Diveplane, not to mention the offerings from incumbents like Google Cloud, Azure and AWS. Now, one South Korean MLOps platform called VESSL AI is trying to carve out a niche for itself by focusing on optimizing for GPU expenses using hybrid infrastructure that combines on-premise and cloud environments.
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