What does RAG at scale look like? When building your own copilot, how do you know your application is delivering the responses as designed? Join our session with AT&T, where Mark will share how they built a RAG knowledge management platform on Azure AI Search, powering hundreds of GenAI applications across the organization. We will show how RAG quality is measured, and the variety of use cases built on top of this RAG platform. See what RAG at scale truly looks like in production.
Mark Austin
Vice President - Data Science
Dr. Austin currently manages a team of ~250 Data Science and developers in the Chief Data Office applying AI, machine learning and automation with applications across many areas of the company such as Fraud, Field Operations, Consumer, Security, Supply Chain, and Corporate functions. His team has developed innovative solutions for large scale routing problems, implemented closed loop AI classification systems and recommendation engines, operationalized computer vision, and improved process and people productivity by deploying an operating >3,000 BOTS company-wide. With more than 29 years of experience, Dr. Austin has also held a variety of leadership and staff roles in running technology planning operations across South Florida, Puerto Rico and the Southeast.
Dr. Austin has chaired various industry technical standards committees, is the co-author on 5 books, has published more than 20 reviewed technical papers, been granted over 100 patents, and is on a number of advisory boards in academia. He holds a bachelor's degree in electrical engineering from the University of Maryland (summa cum laude), a doctor of philosophy degree in electrical engineering from Georgia Tech and is the recipient of the Sigma Xi Thesis Award for his research on various topics related to optimizing cellular systems. He enjoys running, cycling and boating and is based in Plano, Texas.
Dr. Austin has chaired various industry technical standards committees, is the co-author on 5 books, has published more than 20 reviewed technical papers, been granted over 100 patents, and is on a number of advisory boards in academia. He holds a bachelor's degree in electrical engineering from the University of Maryland (summa cum laude), a doctor of philosophy degree in electrical engineering from Georgia Tech and is the recipient of the Sigma Xi Thesis Award for his research on various topics related to optimizing cellular systems. He enjoys running, cycling and boating and is based in Plano, Texas.
Ben Tezcan
Principal Program Manager
Ben Tezcan is a Principal Program Manager at Microsoft, contributing to the future of Azure AI Search.