Vyoma Gajjar
Vyoma Gajjar is an AI Technical Solution Architect with over a decade of experience in AI governance, generative AI, and machine learning. She has worked extensively on developing scalable AI solutions and governance frameworks for global industries, focusing on highly regulated sectors like finance and healthcare. Vyoma is passionate about ethical AI practices and responsible innovation, frequently speaking at major conferences and serving as a mentor to aspiring AI professionals. She holds a patent in AI and actively contributes to shaping the future of trustworthy AI technologies.
Sessions
As large language models (LLMs) become increasingly integrated into industries like finance, healthcare, and law, ensuring their responsible deployment is critical—particularly in highly regulated environments. These industries face unique challenges, including data privacy, compliance with strict regulations, and minimizing the risks of biased or untrustworthy outputs.
This session will explore the complexities of using LLMs in regulated industries and present a governance framework to address these challenges. We'll cover practical solutions for deploying LLMs while adhering to industry-specific regulations, ensuring transparency, reducing bias, and maintaining data privacy. Attendees will learn how to implement governance best practices at various stages of the LLM lifecycle—from model training and validation to deployment and ongoing monitoring.
Drawing on real-world examples and lessons learned, this talk will equip data scientists, machine learning engineers, and AI leaders with actionable strategies for navigating regulatory compliance and minimizing risks, while still harnessing the full potential of LLMs to drive innovation.