Sovereign AI That Actually Works

Everyone's talking about "sovereign AI," but most of it doesn't survive contact with a real business problem. Here's how to actually build AI you own and control, from data to models to compute. In this whiteboard explainer, Great Wave AI's Jack Perschke breaks down how organisations really use AI across five layers: the problem owner, the problem, the application layer (ChatGPT, Claude, Gemini), the models, and the compute underneath. The catch: real organisational work - like reviewing case files for completeness, compliance, and next actions — can't just be dumped into a chatbot. And the two usual fixes both break down. Waiting to hand your sensitive data to OpenAI or Anthropic runs straight into trust, control, and regulatory problems. Paying millions for a bespoke build leaves you with something that's out of date the moment the models move on — back to square one. The alternative is orchestration: a model- and compute-agnostic layer that lets you build AI workflows, connect your own data, swap models freely, and run it all on infrastructure of your choice — without armies of developers or consultants, and with the testing and regression checks built in. You keep control. That's sovereign AI that actually works. Chapters (approx.): 0:00 The five layers of how organisations use AI 0:47 The application layer + a simple example 1:47 When it gets real: regulated orgs and case-file review 2:37 Why you can't just hand the problem to a model 2:55 Approach 1: waiting to hand over your data (and why it stalls) 4:05 Approach 2: bespoke builds — expensive and stale on arrival 5:37 The orchestration answer 6:35 Staying in control: model- & compute-agnostic, testing built in 7:22 Run it in your own environment — no lock-in 7:52 Wrap-up Great Wave AI lets you build, test, and own AI workflows across any model and any compute. 🔗 Connect with Jack:   / jackperschke   Subscribe for more plain-English explainers on making AI actually work in the enterprise. — What is sovereign AI? Sovereign AI means keeping control and ownership of your AI stack — your data, the models you use, and the compute they run on — instead of handing it to a third party. Jack argues the practical route is model- and compute-agnostic orchestration, so you can switch models and infrastructure freely while keeping data and workflows in your control. #SovereignAI #AIOrchestration #EnterpriseAI #GreatWaveAI #JackPerschke #DataSovereignty #LLM #ModelAgnostic #RegulatedIndustries #AIStrategy