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ABOUT THE SPEAKER:
Syed Shariyar Murtaza is an AI leader and innovator specializing in applied machine learning for life insurance, enterprise workflows, and intelligent systems. As an AVP of AI at Manulife Financial, he focuses on building real-world agentic AI solutions that transform business operations and decision-making. His work spans converting complex domain knowledge into executable workflows, designing advanced LLM-based underwriting systems, and creating benchmark datasets for evaluating AI in regulated environments. Shariyar holds a Ph.D. in Computer Science from the University of Western Ontario and is also an adjunct faculty member at Toronto Metropolitan University, where he teaches natural language processing and data science.
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ABSTRACT:
Retrieval-augmented generation (RAG) enables generative AI models to extract accurate facts from external unstructured data sources. For structured data, RAG can be further enhanced with function (tool) calls to query databases. This paper presents an industrial case study of implementing RAG in the call center of a large financial institution. The study outlines the architecture and practical lessons learned from building a scalable RAG deployment. It also introduces enhancements for retrieving facts from structured data sources using data embeddings, achieving both low latency and high reliability. Our optimized production application demonstrates an average response time of only 7.33 seconds. Additionally, the paper compares various open‑source and closed‑source models for answer generation in an industrial environment. This paper is published in the prestigious NAACL (North American Chapter of the Association for Computational Linguistics) conference: https://aclanthology.org/2025.naacl-industry.48/
WHAT YOU’LL LEARN:
Business Leaders: C-Level Executives, Project Managers, and Product Owners will get to explore best practices, methodologies, principles, and practices for achieving ROI.
Engineers, Researchers, Data Practitioners: Will get a better understanding of the challenges, solutions, and ideas being offered via breakouts & workshops on Natural Language Processing, Neural Nets, Reinforcement Learning, Generative Adversarial Networks (GANs), Evolution Strategies, AutoML, and more.
Job Seekers: Will have the opportunity to network virtually and meet over 30+ Top Al Companies.
Ignite what is an Ignite Talk?
Ignite is an innovative and fast-paced style used to deliver a concise presentation.
During an Ignite Talk, presenters discuss their research using 20 image-centric slides which automatically advance every 15 seconds.
The result is a fun and engaging five-minute presentation.
You can see all our speakers and full agenda here