Large Language Models (LLMs) offer unprecedented opportunities to accelerate software development, but for organizations handling sensitive code, public AI APIs are a compliance minefield. When data confidentiality and regional sovereignty are non-negotiable, how do you scale AI assistance to a globally distributed team?
In this talk, we share Linaro’s ongoing journey of designing, deploying, and adopting a multi-tier, on-prem, and regional LLM cloud-node infrastructure. We will dive into the architectural compromises made, the open-source AI toolkits we leveraged, and how we balanced privacy with scalability. Beyond the tech stack, you will learn how we measure developer adoption, track success metrics, and draw real-world lessons from the transition from design to daily developer use. Attendees will walk away with a practical framework for building their own confidential AI infrastructure.
