Milan Parikh is an Enterprise Solution Architect and technology leader specializing in AI-driven cloud architectures, Microsoft Fabric, Power Platform, Azure serverless platforms, and enterprise data modernization. He works at the intersection of artificial intelligence, distributed systems, and low-code engineering, helping organizations design scalable, autonomous cloud operations grounded in strong data foundations.

With more than 15 years of experience working with organizations across many industries, including Fortune 500 companies, Milan has led large-scale digital transformation programs that modernize legacy platforms into event-driven, serverless, AI-ready ecosystems. His work focuses on building intelligent operational architectures that combine Microsoft Fabric, Power Platform, Microsoft Dynamics 365, Azure Functions, Logic Apps, and Dataverse with AI agents to enable self-healing workflows, predictive insights, and real-time decision automation. He has delivered end-to-end solutions where Dynamics 365 drives core business process automation, Power Platform enables rapid low-code development and citizen-led innovation, and Microsoft Fabric unifies data engineering, analytics, and AI workloads into a single governed platform.

Milan is a Fellow of the British Computer Society (FBCS), Fellow of IETE (FIETE), Senior Member of IEEE (SMIEEE), and Distinguished Fellow of the Soft Computing Research Society. He serves as a technical program committee member, reviewer, and keynote speaker at international conferences, contributing research and thought leadership in AI governance, data architecture, and low-code engineering at scale. He is also a Lead Enterprise Data Architect at Cytel, where he applies this expertise to drive measurable business outcomes across complex enterprise environments.

Beyond enterprise architecture, Milan actively mentors engineers and citizen developers, having guided many professionals in building governed, production-grade automation solutions. His work bridges academic research and industry execution, translating complex AI and cloud engineering concepts into practical, repeatable enterprise patterns.