Needs •Cloud-hosted AI Training / Inference•Secure private connectivity to the Cloud•Performant access to Large LanguageModels (LLMs) i.e., RAG•Scalable footprint to support growth Challenges •Cost-effective training & inference for AI Models•Transfer speed of large data volumes•Integrating Public Cloud infrastructure•Managing end-to-end AI workflows Actions •Establish direct connections to Public Cloud•Connect to your private infrastructure•Deploy your private infrastructure in colocation•Operationalize Digital Infrastructure Hub Benefits •Cloud-adjacent colocation reduces latency•Performant throughput reduces latency•Security and compliance for data•Scalability of hosted GPUs for AI processing