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This conference talk explores how to implement platform engineering and developer experience (DevEx) practices for on-premises Large Language Models (LLMs) when cloud or SaaS solutions aren't viable due to data confidentiality concerns. Learn how to set up an internal development platform around a self-hosted LLM on Kubernetes that satisfies both executive demands for AI implementation and security requirements. The presenters demonstrate a live setup of an entire internal development platform for GenAI applications using open source tools, featuring "paved paths" for knowledge integrations (RAG), API integrations with business applications, and quality assurance tooling like the LLM-as-a-judge pattern. Discover practical lessons learned from production implementation that can help balance the needs of CEOs, CISOs, and development teams when deploying on-premises AI solutions.
