Data sovereignty
Your AI runs on your hardware. PHI never leaves your network.
We deploy local language models on your servers or private VPC. No Anthropic API keys for PHI. No OpenAI terms of service for clinical data. Your compliance team says yes on the first read.
What we deploy
Six infrastructure configurations.
Local LLM deployment
Llama 3, Mistral, Phi, or your preferred model running on your GPU server or VPC. No API calls for sensitive data.
Private AI inference server
Ollama, vLLM, or LMStudio configured for your workload. Auto scaled on your hardware or a private cloud you control.
Self hosted vector database
Qdrant, Weaviate, or pgvector on your infrastructure. RAG pipelines that don't route your data through external APIs.
Air gapped AI environment
Full AI stack deployed with no internet connectivity. For high security environments: HIPAA, CJIS, and DoD adjacent workloads.
Private VPC AI infrastructure
AWS, GCP, or Azure private networking with AI workloads fully isolated from the public internet. BAA available with all major clouds.
On prem EHR AI integration
AI features that read from and write to your EHR over your local network. Epic FHIR, HL7, and proprietary connectors.
How it works
From discovery to running model in four steps.
Infrastructure audit
We review your existing hardware, network, and compliance requirements. We spec what you need before any purchase.
Hardware and environment setup
We size and configure the GPU server or private VPC. Drivers, OS, and security controls set up per your compliance requirements.
Model deployment and testing
We deploy the model, run inference benchmarks, and confirm latency meets your workflow needs before integration begins.
Integration and handoff
We connect the model to your EHR or internal tools. Your team gets a runbook. We stay on for 30 days to handle edge cases.
The stack
What we work with.
Ollama
Local model serving. One command to run Llama 3, Mistral, Phi.
vLLM
High throughput GPU inference for production workloads.
Qdrant / pgvector
Vector search that stays on your infrastructure.
NVIDIA / AMD GPUs
Procurement guidance and driver configuration included.
When NOT to use this service
On prem isn't always the right call.
Your data isn't sensitive.
If your workflows don't involve PHI, classified records, or proprietary data you can't share, a private VPC costs more than it saves. A cloud API is cheaper and faster.
You need to move in two weeks.
Hardware procurement and configuration takes 4 to 8 weeks. If you need AI workflows running this month, start with a cloud build and migrate later.
You don't have dedicated IT support.
On prem infrastructure needs someone to restart it, patch it, and monitor it. If that person doesn't exist at your practice, the managed infra retainer is the right path.
Investment
On prem AI pricing.
Infra audit
$2,000 to $4,000
We assess your current setup and spec the hardware or cloud config needed. Written deliverable.
Full deployment
$10,000+
Hardware spec, procurement, installation, model tuning, and integration with your existing systems.
Managed infra
$1,500+/mo
We keep the models updated, monitor performance, and respond to incidents. 99.9% uptime SLA.