Stream: Virtual Room 7
Time: 11:15 - 12:00
As the complexity of the mainframe environment grows and the expertise gap widens, organizations need more than just a chatbot—they need a digital teammate. This session introduces IBM watsonx Assistant for Z, a revolutionary solution that marks the transition from traditional conversational AI to Agentic AI. Unlike standard assistants that simply respond to queries, Agentic AI uses a goal-oriented framework to independently plan, reason, and execute multi-step workflows across the entire IBM Z ecosystem. We will explore the core pillars of this unified framework, including Retrieval-Augmented Generation (RAG) for zero-hallucination responses and the Model Context Protocol (MCP) for secure, authorized automation.
Vineet Dumir is a Senior Solution Architect for AI on IBM Z, collaborating with clients to guide and accelerate their AI adoption journeys. His primary focus is on introducing IBM’s AI product offerings and helping clients effectively apply them to real-world business use cases.
He brings deep expertise in machine learning, artificial intelligence, and data engineering, along with strong hands-on experience across the Hadoop ecosystem and AWS services including EC2, VPC, S3, and Redshift. With extensive experience as a DB2 Database Administrator and DB2 Systems Programmer on the z/OS mainframe platform, Vineet has also led multiple initiatives centered on mainframe and legacy system modernization.
Anil Kumar Puvvadi is a Principal Software Engineering Manager at Microsoft with over two decades of experience delivering highly reliable and scalable platforms across cloud services, big data, and distributed systems. He currently leads the Azure DNS Recursive Resolver team, where he launched the Azure DNS Private Resolver globally and introduced advanced security products such as Security Policy and threat intelligence solutions to protect DNS infrastructure against malicious domains. His leadership also brought to market a Linux-based recursive resolver serving both Microsoft’s first-party and third-party customers at scale. Earlier at Microsoft, Anil built the platform team from the ground up to deliver the Bonsai AI cloud platform, enabling training of AI workloads with diagnostics, metrics, and simulation support through Azure Marketplace. Prior to Microsoft, he led development of a large-scale log ingestion framework at Oracle, worked with AIG on risk analytics platforms, and consulted with Emirates Airlines on critical operational systems. Anil holds a Master’s in Computer Science from Cornell University and a Bachelor’s in Information Science from BMS College of Engineering, Bangalore. His contributions have been recognized with multiple awards, including Microsoft’s organization-level award for Bonsai AI, Oracle’s Excellence Award for Data Ingestion, and several leadership awards at Mindtree.
I am a Solution Architect specializing in Generative AI, enterprise AI adoption, and mainframe modernization. My work focuses on bringing AI capabilities into mission-critical systems, particularly on IBM Z platforms, helping organizations unlock new value from their core infrastructure.
I come from a strong background in mainframe performance engineering and capacity planning, where I’ve worked extensively on analyzing, optimizing, and scaling high-volume transactional systems. This experience has given me deep expertise in performance tuning, workload management, and ensuring reliability in large-scale enterprise environments.
In my current role, I work on integrating Generative AI and intelligent automation into traditional systems, bridging the gap between legacy architectures and modern AI-driven solutions. I’m actively involved in designing scalable AI use cases on IBM Z, including areas like observability, predictive analytics, and operational intelligence.
I’m passionate about helping enterprises evolve their mainframe strategy by combining the stability of existing systems with the innovation of AI and cloud-native technologies. I also enjoy engaging with the broader tech community, sharing insights on how AI can be adopted in regulated and high-performance environments.
Click here to give some Feedback so we can make it even better next year!