Private AI on infrastructure you control.
We deploy language models, RAG systems and AI agents on your own infrastructure, so you can use AI with sensitive data and predictable costs.
What changes for your business.
Data stays private
Prompts and documents never leave your infrastructure.
Answers from your documents
RAG systems that cite the source of every answer.
Predictable costs
No per-token surprises; capacity sized to your usage.
Measured quality
Latency, cost and answer quality tracked over time.
What we deliver.
Everything you need from private ai, from first assessment to day-to-day operations.
- Private LLM deployment with Ollama and vLLM
- GPU inference infrastructure, cloud or on-premises
- RAG pipelines on Qdrant vector databases
- AI agents with Dify and LangChain
- Workflow automation with n8n
- Monitoring of latency, cost and answer quality
A clear path from first call to running platform.
- 01WorkshopPick the use cases with real business value.
- 02PrototypeProve quality on your own data.
- 03ProductionDeploy securely with access control.
- 04OperateMonitor, evaluate and improve.
Frequently asked questions
Which models can you run?
Open-weight models such as Llama, Mistral, Qwen and Gemma, chosen for your use case, languages and hardware budget.
Do we need our own GPUs?
Not necessarily. Models can run on cloud GPU instances, dedicated servers or your own hardware, depending on volume and privacy needs.
Can the assistant use our internal documents?
Yes. A RAG system indexes your documents and answers with references, while access rules keep sensitive content restricted.
Tell us what you run today. We’ll help you run it better.
A 30-minute call with an engineer, not a sales script. You leave with concrete next steps, whether or not we work together.