Industry partners have a unique opportunity to enable agent experiences that address critical jobs-to-be-done across domains. Better precision and higher quality outcomes can be achieved when agent experiences are built with a deep understanding of industry- and role-specific needs. In this session, we will provide three demos focusing on industry components that accelerate agent experiences for customers and partners: industry AI model enablers, an agent for financial insights, and a new Teams app for financial services meeting preparation.
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Jeremy Reynolds
Principal Group Applied Scientist Manager
Jeremy leads a US-based applied science team responsible for developing industry-adapted generative AI systems. Before joining Microsoft, he led research labs in startup and academic environments. He has a PhD in cognitive neuroscience from Washington University and an undergraduate degree from Georgia Tech.

Eitam Sheetrit
Data and Applied Sciences Manager
Eitam is a Data & Applied Sciences Manager at Microsoft ISVAI, holding a Ph.D. in Information Systems Engineering with a specialization in cyber-security and healthcare. Eitam leads pioneering pre-training initiatives for industry-specific language models and drives cutting-edge research in this domain. Additionally, Eitam oversees Responsible AI efforts, ensuring ethical AI practices, governance, and compliance throughout the organization. As an academic lecturer, Eitam shares expertise and passion for AI with the next generation of researchers. Eitam also serves as a reviewer for top-tier conferences such as ICML, KDD, NeurIPS, and ICLR.

Ilya Venger
Principal Product Lead - Industry AI
Ilya leads a Product Management team, focusing on Industry AI. The team defines foundations and accelerators across Microsoft Clouds for generative AI copilots across various industries, including Financial Services, Manufacturing, Retail, and more. These Industry AI copilot accelerators enable customers and partners to build high-quality copilots, extend Microsoft Copilot, and enhance them with their own structured and unstructured data.