Session

MLOps That Ships: Accelerating AI Deployment at Vizient with Databricks

Overview

ExperienceIn Person
TypeBreakout
TrackArtificial Intelligence
IndustryEnergy and Utilities, Health and Life Sciences, Financial Services
TechnologiesMLFlow, AI/BI, Databricks Workflows
Skill LevelIntermediate
Duration40 min

Deploying AI models efficiently and consistently is a challenge many organizations face. This session will explore how Vizient built a standardized MLOps stack using Databricks, Azure DevOps and GitHub Actions to streamline model development, deployment and monitoring.

 

Attendees will gain insights into how Databricks Asset Bundles were leveraged to create reproducible, scalable pipelines and how Infrastructure-as-Code principles accelerated onboarding for new AI projects.The talk will cover:

  • End-to-end MLOps stack setup, ensuring efficiency and governance
  • CI/CD pipeline architecture, automating model versioning and deployment
  • Standardizing AI model repositories, reducing development and deployment time
  • Lessons learned, including challenges and best practices

 

By the end of this session, participants will have a roadmap for implementing a scalable, reusable MLOps framework that enhances operational efficiency across AI initiatives.

Session Speakers

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Ram Radhakrishnan

/Director - Technology, Data & Analytics
Vizient

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Adam Hasham

/Lead Machine Learning Engineer
Vizient