AWS Public Sector Blog
Author: Yunjie Chen
Yunjie is a Principal Customer Solutions Manager (CSM) within the AGS SWAT team at Amazon Web Services (AWS). She integrates deep technical architecture with strategic leadership to unlock the transformative potential of generative AI within complex, mission-critical environments. With a track record of driving success for major public sector and enterprise customers, Yunjie specializes in leading Generative AI Experience-Based Accelerators (EBAs) and high-stakes technical engagements. She is dedicated to bridging the gap between cutting-edge AI research and scalable production, ensuring that innovations in agentic workflows and multi-cloud strategy deliver tangible business value.
The transformative impact of generative AI on business workflows in a highly regulated industry
The aerospace industry represents one of the most complex regulatory environments for software development, where system failures can result in catastrophic consequences including loss of human life and multibillion-dollar assets. In this blog post, learn how Blue Origin operates within this framework, in which software systems control every aspect of rocket propulsion, navigation, life support, and mission-critical operations.
Unlocking the power of generative AI: The advantages of a flexible architecture for foundation model fine-tuning
A flexible architecture is a crucial factor in unlocking the full potential of generative artificial intelligence (AI) solutions. In this post, we cover an Amazon Web Services (AWS) Cloud infrastructure with a modular architecture that enables you to explore and take advantage of the benefits from different open source foundation models in a flexible way. This solution provides several benefits.
Use modular architecture for flexible and extensible RAG-based generative AI solutions
In this post, we cover an Amazon Web Services (AWS) Cloud infrastructure with a modular architecture that enables you to explore and take advantage of the benefits from different Retrieval-Augmented Generation (RAG)-based generative AI resources in a flexible way. This solution provides several benefits, along with faster time-to-market and shorter development cycles.