Mr. Rajesh Sura

Architecting Trust and Intelligence: Building Scalable, AI-Driven Data Platforms for the Enterprise

Abstract: 

In today’s hyper-connected, data-rich enterprise landscape, success hinges not just on access to data—but on the ability to extract actionable, trustworthy intelligence at scale. Data platforms are no longer operational backbones—they are strategic catalysts for innovation, growth, and competitive differentiation. This keynote explores the future of enterprise analytics through the lens of trust, intelligence, and architectural scalability. 

Drawing on over 15 years of global leadership in data engineering and AI strategy, I will share proven frameworks for architecting next-generation platforms that unify artificial intelligence with business intelligence (BI). Attendees will learn how to embed trust through metadata-driven governance, enhance decision velocity via explainable machine learning, and democratize insight access through natural language processing.

The session will also address the critical role of ethical design, regulatory alignment, and compliance-by-default as organizations scale AI systems across regions and functions. Real-world case studies will illustrate how these principles have powered AI transformation for large enterprises—supporting millions of users, accelerating vendor onboarding, and unlocking billions in business value. 

Whether you're a data strategist, platform architect, or enterprise innovator, this keynote offers a forward-looking blueprint for building intelligent, resilient, and trusted analytics ecosystems—designed not just for scale, but for impact.

Profile: 

Rajesh Sura is a global leader in data engineering, AI strategy, and advanced analytics, with over 15 years of experience architecting large-scale data platforms and intelligent systems that drive measurable business and societal impact. With certifications from MIT, AWS, and SAP, Rajesh is known for driving innovation in enterprise data architecture, ML integration, data democratization through natural language analytics, and data governance frameworks across high-velocity environments. He is passionate about mentoring future data leaders, and applied research.