Engineering & Infrastructure
Private AI Deployment
3–8 weeksAI inside your perimeterDemo
Everything runs on your networkNothing leaves to public services
Data on your network
100%
nothing leaves to third parties
Latency
240 ms
on-premise
Data residency
Your region
meets local compliance
For companies in regulated sectors — financial, healthcare, government, legal — sending data to cloud AI services is not always an option.
We deploy complete AI systems within your controlled infrastructure: local LLMs, on-premise computer vision, and ML pipelines that operate entirely within your security perimeter, with no third-party dependency. Technically: deployment of open-weight models (LLaMA, Mistral, Qwen) with Ollama or vLLM, quantization for efficient inference on available hardware, internal inference APIs, security architecture documentation, and model update guide.
Use cases
- —You need internal assistants or models without sending sensitive data to third parties
- —You want to run computer vision inside private infrastructure
- —You have compliance requirements that demand on-premise or isolated pipelines
- —You want to tune models on proprietary data within a controlled environment
Deliverables
- —AI stack deployed on client's private infrastructure
- —Hardware specification and sizing recommendations
- —Security architecture documentation
- —Internal inference API
- —Performance comparison vs. cloud alternative
- —Model update and maintenance guide
Your data never leaves your environment
We deploy the models inside your own infrastructure. Your data is never sent to public LLMs or third parties.
Your infrastructure
Your dataPrivate AI
Public LLMs · third parties