Presented by
Catalina Herrera, Principle Sales Engineer, and Chris Helmus, Sr. Sales Engineer @ Dataiku
De-Risk Your AI Efforts by Removing Friction From Your MLOps Processes
About this talk
According to McKinsey, building ML into processes enables leading organizations to increase their process efficiency by 30% or more while also increasing revenues by up to 10%. However, it’s not that simple. Several blockers prevent organizations from overcoming the difficulties encountered when industrializing AI. As a result, it can take up to nine months for teams to go from the proof of concept stage to production. In this context, how do you remove friction from your MLOps process and make your model processes trusted, agile, and controlled, so that you can finally deliver more value from your analytics and model faster? In this session, you’ll learn how Dataiku’s MLOps framework can help you to:
-Increase agility and solve difficulties in handoffs between business, data scientists, and IT
-Make your models trusted from the get go (and, therefore, reduce risk)
-Apply model control and approvals to enable, not disable, your AI projects
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Dataiku is the platform for Everyday AI, enabling data experts and domain experts to work together to build data into their daily operations, from advanced analytics to Generative AI. Together, they design, develop and deploy new AI capabilities, at all scales and in all industries. Organizations that use Dataiku enable their people to be extraordinary, creating the AI that will power their company into the future.
More than 600 companies worldwide use Dataiku, driving diverse use cases from predictive maintenance and supply chain optimization, to quality control in precision engineering, to marketing optimization, Generative AI use cases, and everything in between.