Mr. Santosh Nakirikanti

Semantic Ranking and Intent Modeling: AI Architectures for Search Relevance

Abstract:

Traditional keyword-based search systems struggle to understand user intent, leading to irrelevant or low-value results. In this talk, I will explore how modern AI techniques, such as semantic embeddings, neural ranking models, and context-aware query processing transform enterprise search into an intelligent, adaptive experience. We’ll discuss architectural patterns that integrate dense retrieval, reranking pipelines, and real-time personalization into scalable systems. Drawing from real-world implementations and research-backed methods, this session bridges the theory of semantic representation with practical approaches to improving search accuracy, intent alignment, and user engagement in digital commerce.
 

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.