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Utilizing AI Ep. 9: Deploying AI Models in the Enterprise

Stephen Foskett discusses the practicalities involved in packaging, deploying, and operating AI models with Manasi Vartak of Verta. Deploying an AI model in production is a challenge, just like it was in the past with software. Once a company has an AI model to deploy, they must validate its results, create scaffolding code to make it consumable, optimize the data pipelines, instrument it, and assign operators. This is what Manasi and Verta have developed, and the world of AIOps parallels that of DevOps but with some unique twists. The data component of AI models presents a unique challenge not found in some other enterprise applications, and it is important to continually test the model to ensure that it hasn’t drifted off target as data changes. Previously, training models were the main challenge for AI, but now it’s all about getting things into production. That’s why we started this podcast and why we created AI Field Day!

This episode features:

Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett

Manasi Vartak, CEO and Founder of Verta (@VertaAI). Find Manasi on Twitter at @DataCereal

About the author

Gestalt IT Staff

Gestalt IT Staff posts are a collective effort, providing the best analysis and commentary from leaders in the fields of virtualization, networking, storage, and desktop engineering.

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