Karthik Kappaganthu

I’ve spent the last 15+ years working across multiple waves of AI and Machine Learning — from classical ML systems and recommender systems to large-scale enterprise AI platforms and now Agentic AI systems. Over the years, I’ve had the opportunity to work across research, product development, and enterprise transformation at organizations including Google, Bain, Livongo, Siemens, and Cummins. This has given me a first-hand view into how AI evolves from research into real-world operational systems — and more importantly, what actually creates enterprise value versus what remains experimentation. I’ve worked on both sides of the AI stack: - building and scaling ML/LLM systems - and helping organizations operationalize them into measurable business outcomes My experience spans: • Enterprise AI architecture • Agentic AI systems and workflows • LLM platforms and orchestration • AI transformation and operating models • Production ML systems and MLOps • Healthcare and operational AI • Intelligent workflow automation A recurring theme throughout my career has been translating advances in AI into systems that improve decision-making, operations, and execution in complex enterprise environments. Today, I’m especially interested in the next phase of enterprise AI: AI systems that can reason, plan, coordinate workflows, and drive operational value with appropriate human oversight and governance.