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Wallaroo Labs Launches in Azure Marketplace; Announces Air Gap Support for Edge Machine Learning Deployment

Wallaroo Labs announced the availability of Wallaroo Enterprise Edition on Microsoft Azure Marketplace. Wallaroo's model operations platform for deploying, observing, and managing machine learning in production enables customers to easily operationalize ML Models with our purpose-built inference engine, advanced observability, and powerful A/B testing capabilities.  Wallaroo is working to join Microsoft's co-sell readiness program by end of the year, furthering the integration and commitment to enabling modern MLOps for Azure customers.

"Even beyond the leading role of Microsoft's venture arm, M12, to our Series A earlier this year, strengthening our relationship with Azure is a priority because we understand how important they are to our shared customer base," said Benny Louie, Head of Partnerships at Wallaroo. "We look forward to continuing to work with Azure to help data teams in industries spanning financial services, manufacturing, public sector, and more to generate real, sustained value from their AI/ML programs."

Additionally, Wallaroo announced the launch of their Air Gap Edge Deploy functionality to make it easy for enterprises to deploy and manage machine learning models at the edge in environments with no IP connectivity, such as oil derricks, gas pipelines, and transmission lines for Energy & Utilities; and autonomous equipment in Smart Manufacturing and Smart Agriculture.

"Our fastest growing opportunity space has been Edge ML as you look at how equipment and facilities are generating more sensor data than ever," said Younes Amar, Head of Product at Wallaroo. "Enterprises are looking to deploy ML at the edge for use cases where latency matters most, such as smart factories, autonomous vehicles, or routing optimization. With our Air gap solution, enterprises can still deliver value from their AI programs even when there is little or no connectivity."
Published Wednesday, September 21, 2022 3:02 PM by David Marshall
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