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CAST AI Raises $10 Million Series A to Accelerate Product Development

Artificial Intelligence (AI) , Machine Learning (ML), Natural Language Processing (NLP), Deep Learning (DL), AI Model, AI-powered Solutions, Digital Transformation, ML Model, Natural Language Understanding (NLU), AI News, Artificial Intelligence News
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A cloud-native application management company – Cast AI™ – specializing in cost optimization for customers running applications on AWS, Microsoft Azure, and Google Cloud, has just completed a $10 million Series A round led by Cota Capital, alongside Samsung Next and additional investors. CAST AI Autonomous Kubernetes cloud management platform will be advanced as a result of the raise.

Yuri Frayman, CAST AI co-founder and CEO, said, “The funding round will accelerate CAST AI product development initiatives and ensure the company’s rapidly growing market position. “We are thrilled to have Cota Capital lead our Series A round. As we continue on our mission to utilize artificial intelligence for optimizing cloud deployments, we will use the additional funds to further accelerate development and delivery of our platform and provide real and measurable value to our customers.”

Despite rising cloud costs for customers, the cloud computing industry is ripe for disruption. Around $17 billion of cloud overspends in 2020 alone were due to incorrect tool selections and a lack of capacity management capabilities. AWS customers have saved 60% to 90% of their annual cloud expenses by utilizing the CAST AI team’s machine learning (ML) platform developed in conjunction with machine learning.

As part of its platform announcement, the company has also added support for both Google Cloud Platform and Microsoft Azure public clouds. CAST AI’s strategy revolves around optimizing and autonomously managing Kubernetes for any cloud service. The instant savings report users receive after connecting to existing clusters can identify cost-saving opportunities immediately.

CAST AI identifies the resources needed for optimal utilization based on the observations and learnings of the cloud environment of a business. Platforms with full automation and the ability to set optimization parameters provide the greatest value to customers. DevOps engineers can focus on more challenging and exciting tasks while CAST AI handles the low-level optimizations.

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