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The healthcare industry is increasingly adopting AI, but many payers and providers struggle to turn data into actionable insights. Our research report, Healthcare payers and providers: Lean into data mastery to extend patient-centered care and promote health equity, by Alok Mandal, Global Head – HLS Consulting at Virtusa, reveals key gaps in data strategy, AI adoption, and data quality that limit patient-centered care and progress toward health equity. Read the report for expert insights: https://splr.io/6047tiGo9 #VirtusaResearchCenter #DataStrategy #DataInsights #CustomerExperience #PatientCentricity

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Virtusa has been positioned as a Leader in the ISG (Information Services Group) Generative AI Services 2025 report for its strategy and deployment services powered by the Helio platform. "Virtusa blends vertical-aware consulting with engineering depth, using its AI Lab and Helio platform to guide clients from GenAI strategy to production through platform-linked workshops and industry-aligned innovation journeys," said Gowtham Kumar Sampath, Analyst, ISG. Read the full news: https://lnkd.in/dqPACV5C #GenerativeAI #AI #DigitalTransformation #ITServices #Consulting #TechLeadership #TechIntelPro

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The challenge isn't just automating pre-authorization, it is building systems that understand clinical context, regulatory nuance, and patient urgency simultaneously. That is where agentic AI architectures make the difference. When we talk about "empowering clinicians to act faster," we are really talking about intelligent orchestration: AI agents that can reason across policy documents, clinical guidelines, and member data in real-time, then route decisions to the right stakeholders with full transparency. This is the future we are building across our Healthcare Payer systems that don't just process faster, but think smarter. Worth watching for anyone working at the intersection of AI and healthcare operations. Valuable insights Babu Dhandapani #HealthcareAI #AgenticAI #HealthTech #citiusTech #Knewron

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How did we used Domain Driven Design  concept to break down our monolithic system into bounded contexts, and modernize it into cloud-based microservices? Also, how did we implement the bubble context architecture pattern? Read our Engineering Technical blog Credits : Danish Garg https://lnkd.in/dhPSDf4V

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I am happy to share that our research paper has been accepted for publication by IEEE. The paper focuses on a challenge we have seen repeatedly across organizations: scaling machine learning from experimentation to real, sustainable products is still difficult, even with mature teams and modern platforms. In this work, we examine the key inhibitors to ML product scalability and highlight how enterprise IT architecture plays a foundational role in addressing them. The paper also proposes a Machine Learning Product Development Lifecycle that brings together architecture, engineering practices, and organizational design, instead of treating ML as an isolated initiative. From an Enterprise Architecture and technology leadership perspective, a few insights stood out clearly: • Scaling ML is an architecture problem before it becomes a tooling problem • Lifecycle thinking is critical to avoid fragmented pipelines and fragile systems • Architecture must evolve to support continuous learning, governance, and integration with enterprise platforms This research reinforced for me that the role of Enterprise Architecture is expanding, especially as AI and ML move from pilots into core business capabilities. Preprint available here: https://lnkd.in/gVQUh-5k I would be interested to hear how others are approaching ML product architecture and scale in their organizations. #BigIdeas2026 #BigIdeasEnterpriseArchitecture2026 #EnterpriseArchitecture #ArchitectureStrategy #TechnologyLeadership #SystemsThinking #DigitalTransformation #BusinessArchitecture #ITStrategy #LeadershipDevelopment #OrganizationalDesign #StrategyExecution #TechCommunity #InnovationLeadership #AIArchitecture #MachineLearning #MLatScale #AIOps

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Companies struggle to build the case for change, but Capital One saw how technology could reshape the industry and moved to act. Listen as divisional CIO Mark Mathewson walks Steven Breeden through the bank’s decade-long tech transformation and the lessons learned along the way: https://lnkd.in/gy-6KsEt

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Alok Srivastava has been elevated to Senior Director of Software Engineering at Optum, where he leads the strategic mandate for engineering excellence and digital innovation within the global healthcare technology leader. Based in Noida, Alok is responsible for driving large-scale software delivery, fostering a culture of technical high performance, and aligning engineering roadmaps with global business objectives. This promotion marks a significant milestone in his 11-year legacy at Optum Global Solutions, during which he has consistently scaled the leadership ranks from IT Manager to Director of Software Engineering. Before being elevated to this role, Alok established himself as a seasoned technology leader with over two decades of experience in healthcare consulting and technical project management. He spent over eight years at Syntel, where he served as Manager of Healthcare Consulting and Pre-sales, bridging the gap between complex technical solutions and client business needs. His professional foundation was built through foundational engineering roles at Wipro Technologies, where he served as a Project Engineer. By merging his deep expertise in healthcare IT systems with a proven track record of managing multi-functional engineering teams, Alok now spearheads the software engineering leadership mandate for Optum. #cxolanes #HealthTech #LeadershipElevation

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FABCON 2026 in Atlanta was nothing short of mesmerizing-where bold ideas, breakthrough tech, and real-world impact came together seamlessly. An electrifying blend of vision, innovation, and execution that set the tone for the future of data and AI. Now, it’s a wait-and-watch moment to see how much of it proves truly real, scalable, and competitively differentiated. ** AI Foundry: Fabric IQ is positioned as a capability that makes data AI-consumable for agents and AI apps via OneLake ** OneLake Transform transformations are applied on top of shortcut or mirrored data (zero‑copy, zero‑ETL), preserving the original source while exposing a transformed view in OneLake. New Connectors have been added (SharePoint in preview). ** Data and Catalog mirroring / zero copy options across open table formats from snowflake and Databricks into Fabric ** SAP Fabric and Salesforce Fabric version with zero copy and write back functionality ** Availability of CoPilot across various platforms within Fabric exclusively designed to support that platform only ** Fabric AI and Data Agents ** Zero ETL Data Mirroring onto Onelake from Azure data for PostgreSQL. Analytics on Operational workloads made simple. ** Building declarative AI Pipelines made simpler with dspy and pixeltable Thanks to Cognizant leadership for the opportunity. Rajesh SreepadaSatish Hegde FABCON & SQLCON - The Microsoft Fabric & SQL Community Conferences Microsoft Fabric

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