✨ LLM deployment · GPU infra · RAG · local / offline AI
AI Infrastructure
Stand up private, cost-controlled AI infrastructure — self-hosted LLMs, GPU scheduling and RAG — so your data and models stay yours, online or fully air-gapped.
The problem
Where teams get stuck.
- Per-token bills that scale out of control
- Sensitive data sent to third-party APIs
- No GPU strategy — idle spend or starved jobs
- RAG that hallucinates or leaks across tenants
What we deliver
How Resolve fixes it.
- Self-hosted LLM serving (vLLM / Ollama) & routing
- GPU infrastructure, scheduling & right-sizing
- RAG architecture with retrieval you can trust
- Offline / air-gapped AI for regulated environments
- Bring-your-own-model wiring to an existing org LLM
How it fits together
The AI Infrastructure blueprint.
A typical shape — tailored to your estate and delivered on the platform.
🧩Your app
→🔀Model routerpolicy · fallback
→⚡ vLLM
🦙 Ollama
🧠 Your LLM
🎛️GPU poolscheduled
→📚RAG / vectors
→🔒Air-gapped
On the platform
Modules we put to work.
Delivered on the AI Resolve Platform — supervised, secured and yours.
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Outcomes
What you walk away with.
✓
No per-token lock-in
✓
Data and models you fully own
✓
Air-gapped-capable AI delivery
Let’s scope it
AI Infrastructure, delivered in days.
One meeting and we’ll give you a fixed plan — tracked live in your customer portal, on a platform you’ll own.
Start a project → Book a consultation