Choosing between local, private and sovereign AI
The three terms get mixed up constantly. Here is a practical framework to decide what your organization actually needs.
Read moreWe are the consulting agency for private, local and sovereign AI. Deploy capable models inside your own perimeter — without runaway cloud bills or vendor lock-in.
Trusted by teams who keep their data at home
We combine open models, the right hardware and disciplined engineering so you get the capabilities of frontier AI while keeping ownership, compliance and budget under control.
Your prompts, documents and models never leave your perimeter. No third-party training, no data leakage, full auditability.
Read moreRun capable open models on your own hardware or private cloud. Air-gapped deployments and edge inference supported.
Read moreEuropean hosting, transparent supply chain and exit-ready architecture. Stay compliant with GDPR and sector regulations.
Read moreRight-sized models and predictable infrastructure. Cut per-token spend by replacing API bills with assets you own.
Read moreFrom the first workshop to production rollout, we stay hands-on. No black boxes — you understand and own every layer of your stack.
Organizations across finance, public sector and healthcare trust us to keep their AI private and affordable.
“Kaki AI moved our assistant fully on-prem in weeks. We kept the accuracy, removed the vendor lock-in, and our compliance team finally signed off.”
“Sovereignty was non-negotiable for us. They designed an air-gapped stack that our auditors loved — and the running costs dropped sharply.”
“Pragmatic, transparent and fast. They sized the right open models instead of selling us the biggest one. Costs are now predictable.”
Let's scope a private, sovereign and cost-controlled AI roadmap for your organization. The first call is free.
Field notes on private AI, sovereignty and cost control.
The three terms get mixed up constantly. Here is a practical framework to decide what your organization actually needs.
Read moreQuantization, batching and model right-sizing — the levers that reduce inference spend by an order of magnitude.
Read moreHow to ship retrieval-augmented generation with zero outbound network calls and full document traceability.
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