Architecting Resilient Enterprise System Separations with Azure Cloud and AI-Driven Testing

Enterprise IT separation projects driven by mergers, acquisitions, or restructuring represent some of the highest-risk transformation initiatives in large organizations. When deeply integrated systems must be disentangled, traditional testing strategies often fail to account for hidden dependencies, integration debt, and data integrity risks. This session introduces a modern, Azure-powered framework for executing resilient separation programs with AI-enhanced validation and cloud-native testing strategies.

Participants will explore how Azure DevOps, Azure Test Plans, and AI-assisted regression testing models can be combined to automate complex validation cycles across ERP, HR, and financial systems. The session introduces a structured approach to analyzing architectural entropy measuring dependency disorder across business, data, and application layers during system disentanglement.

The proposed framework is built on four pillars: data integrity validation using Azure Data Factory and automated reconciliation pipelines; integration testing across APIs and event streams; performance and stress testing in elastic Azure environments; and business process continuity validation using AI-driven scenario simulation.

The talk also demonstrates how machine learning models can proactively identify high-risk integration points, predict failure probability during cutover windows, and optimize test case prioritization based on impact analysis.

Attendees will gain practical insights into building scalable test environments in Azure, embedding MLOps into transformation programs, and maintaining operational stability during high-risk transitions. Emphasis will be placed on governance, compliance, and automated monitoring to ensure minimal business disruption.

This session is designed for enterprise architects, DevOps leaders, cloud engineers, and transformation program managers seeking to combine Azure cloud capabilities with AI-driven intelligence to de-risk complex system separations.

Accelerating Healthcare IT: The Model Office Approach for Standardized Implementations

The Model Office is a strategic approach designed to streamline
healthcare IT implementations. It focuses on developing standardized,
reusable configurations adaptable across diverse healthcare IT
platforms, directly addressing the core challenges of implementation
complexity and high costs. This innovative and structured framework empowers healthcare payers to accelerate system deployments, ensuring consistent quality and adherence to regulatory compliance.

Texas DynamicsCon Regional

AI Applications in Healthcare Insurance: Digital Transformation and Outcomes

Artificial intelligence offers a transformative solution to these challenges, driving operational excellence while maintaining compliance standards. Early adopters demonstrate measurable improvements in efficiency and cost reduction, making AI crucial for competitive advantage. This session includes Technical Architecture Assessment, Algorithm Performance Analysis and Technical Implementation Roadmap

AI Community Days - This session provides deep technical insights for IT leaders and architects implementing AI solutions, enabling informed decisions for robust and scalable deployments.