CAST AI, the Kubernetes automation and cost-optimization platform, today announced that co-founder and chief product officer Laurent Gil will be a panelist at Cota Connect, a summit hosted by Cota Capital that will gather a community of investors, entrepreneurs, and technology leaders in San Francisco on May 19-20, 2022.

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Cota Capital is a San Francisco-based technology investment firm that partners with exceptional leadership teams to build and grow timeless companies. Over the years, its team of seasoned founders, investors, and operators has built a high-caliber network that offers deep technical and operational expertise to portfolio founders and entrepreneurs looking to bring enduring ideas to life.

The Cota Connect conference will feature several panels covering different aspects of digital transformation and technological innovation. Laurent Gil, CAST AI’s co-founder and chief product officer, will participate in a panel discussion on the future of digital infrastructure, including artificial intelligence. 

“It’s an honor to participate in Cota Capital’s inaugural Cota Connect conference,” said Gil. “CAST AI has always been dedicated to making the cloud as fast, reliable, and cost-effective as possible for our customers. Our partnership with the expert team at Cota Capital has been a large part of making that possible.”

“Cota offers ‘knowledge capital’ to our portfolio companies like CAST AI,” said Bobby Yazdani, co-founder and partner of Cota Capital. “‘Knowledge capital’ is the differentiated combination of financial capital, deep operational expertise, know-how, and a vast industry network we bring to our portfolio companies. To have CAST AI’s co-founder on one of the panels at Cota’s inaugural conference speaks to the strong partnership that has been forged between these two great teams.”

About CAST AI:

CAST AI is the leading Kubernetes automation platform for AWS, Azure, and GCP customers. CAST AI goes beyond monitoring clusters and making recommendations; the platform utilizes advanced machine learning algorithms to analyze and automatically optimize clusters in real time, saving customers 50% or more on their cloud costs, and improving performance and reliability to bolster DevOps and engineering productivity.

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