Mr. Santosh Nakirikanti

AI for Search Relevance: Architectures and Applications

Abstract:

Search systems are rapidly evolving from keyword-based retrieval to AI-driven architectures that understand meaning and intent. This talk explores how semantic ranking and intent modeling enhance relevance, personalization, and user engagement across digital commerce and enterprise search platforms. We will examine the underlying architectures that integrate dense retrieval, reranking pipelines, and context-aware intent inference, as well as practical strategies for deployment at scale. Drawing from research and real-world implementations, the session bridges theory and application, offering insights into how organizations can design and optimize AI-powered search systems that deliver measurable improvements in discovery, conversion, and user satisfaction.

Profile:

I’m a Principal Digital Architect with over 12 years of experience building scalable, enterprise-grade systems across commerce, cloud, and AI. In my current role at Waters Corporation, I lead initiatives focused on AI-driven platforms, digital transformation, and microservices-based architectures. I’ve also contributed to the research and practitioner community through conference talks and publications, particularly in the space of intelligent commerce systems. I enjoy solving real business problems using the latest technologies and building efficient, practical solutions that create impact.