Self-hosted AI & private infrastructure
All your AI — on your servers, under your control.
Running models, agents, and AI tools on private infrastructure — Ollama, vLLM, OpenWebUI, LiteLLM, and more.
Who this is for
- Organizations that can't send data to OpenAI/Anthropic.
- Execs looking at their AI bill asking if there's a cheaper way.
- Developers who want full control over models, versions, and flows.
What you get
- Architecture: which model for which workflow, which GPU, which backend.
- Install: Ollama / vLLM / TGI / LM Studio in your environment.
- Interface: OpenWebUI / LibreChat / a custom one.
- Routing: LiteLLM / OpenRouter to pick a model per request.
- Monitoring, backups, and version updates.
How it works
- 01
POC
Run a small model on one server within a week — we measure response time and cost.
- 02
Production
Right GPU, network, security, backups.
- 03
Integration
Interface for employees, API for apps.
- 04
Maintenance
Model updates, monitoring, usage reports.
FAQ
Which open models are worth running?
Depends on the task. Llama 4 / Qwen / Mistral / Mixtral / DeepSeek — each excels at something different. We benchmark on your cases, not on hype.
How is this different from OpenAI?
Privacy, predictable cost, control over versions. For many business tasks open models are good enough — and dramatically cheaper.
Do I need an expensive GPU?
Not always. For non-critical tasks an RTX 4090 or a Mac Studio works. For heavy workloads — H100 / MI300.
Want to see what you could run in-house?
A short call is enough to build a first estimate: which model, which hardware, monthly cost.