AI Sovereignty Training in Provo

This instructor-led, live training in Provo (online or onsite) is aimed at system administrators and DevOps engineers who wish to deploy, configure, and manage EXO clusters for private LLM inference across multiple Apple Silicon or Linux nodes.

This instructor-led, live training in Provo (online or onsite) is aimed at DevOps engineers and infrastructure architects who wish to automate the provisioning, monitoring, and lifecycle management of private AI clusters built on EXO.

This instructor-led, live training in Provo (online or onsite) is aimed at security engineers and compliance officers who wish to harden EXO deployments, control model access, and govern AI workloads running entirely on-premise.

This instructor-led, live training in Provo (online or onsite) is aimed at developers and technical teams who wish to use Ollama and open models to build and run private agentic AI solutions on internal infrastructure.

By the end of this training, participants will be able to: install and configure Ollama, evaluate and run open models locally, create simple agentic and retrieval-based workflows, and apply security and governance controls for regulated environments.

Ollama is an open-source tool for running large language models locally on consumer and enterprise hardware. It abstracts model quantization, GPU allocation, and API serving into a single command-line interface, enabling organizations to self-host LLMs like Llama, Mistral, and Qwen without sending prompts or data to OpenAI, Anthropic, or Google.

This instructor-led, live training in Provo (online or onsite) is aimed at intermediate-level IT leaders, compliance professionals, security teams, and enterprise architects who wish to use sovereign AI principles and governance practices to design AI environments that protect sensitive data, support localization requirements, and reduce vendor lock-in.

By the end of this training, participants will be able to: explain sovereign AI concepts, evaluate hosting and governance options, define controls for prompts and logs, and create a practical adoption roadmap.