Mr. Vivek Venkatesan

Decoding Context and Intent: Building Intelligent Data Pipelines for Real-Time Insight

Abstract:

In today’s fast-paced digital ecosystems, raw data is no longer enough—understanding context and intent has become critical to delivering actionable insights and intelligent user experiences. This keynote explores how modern data pipelines can evolve from traditional ETL frameworks into context-aware, intent-driven systems using applied AI and large language models (LLMs). Drawing from real-world implementations—including behavioral analytics and AI-integrated pipelines developed at scale—this session will demonstrate how to capture deeper meaning from user sessions by enriching data with semantic context, user journey summaries, and inferred intent. We'll walk through how tools like AWS Glue, Snowflake, and LLM APIs can be orchestrated to support this transformation in a scalable and interpretable way. Attendees will gain practical insights into: Designing data flows that go beyond metrics to deliver human-readable understanding Using LLMs to annotate behavior with intent, top dwell reasons, and session insights Addressing challenges around performance, explainability, and adoption Whether you're a data scientist, AI practitioner, or decision-maker, this talk offers a blueprint for turning complex interaction data into real-time intelligence that drives better decisions, personalization, and automation.

 

Profile:

 

Vivek Venkatesan is a Lead Data Engineer and Distinguished Engineer at The Vanguard Group, one of the world’s largest investment management firms. With over 15 years of experience in data engineering, AI integration, and scalable cloud architectures, he has led high-impact digital transformation initiatives across healthcare, insurance, and finance.

Vivek’s work during the COVID-19 pandemic included designing a real-time exposure alerting system for a major healthcare organization—preventing workplace infections using intelligent data flows. At Vanguard, his innovations have resulted in over $250,000 in annual infrastructure savings while advancing real-time decision intelligence. He actively mentors engineers, contributes to AI-driven frameworks, and serves as a peer reviewer for international conferences including FTNCT and CONIT.