On-Prem AI
Your AI, your servers, your rules
Deploy powerful open-source AI models on your own infrastructure. No data leaves your network, no per-query API bills, and no dependency on third-party providers. Full sovereignty, full control.
What you get
Hardware assessment
We evaluate your existing servers or recommend the right hardware. GPU selection, memory, storage — all sized to your workload.
Model selection & tuning
We pick the right open-source model for your use case (Llama, Mistral, Phi, etc.) and fine-tune it on your domain data.
Deployment & orchestration
Production-grade setup with load balancing, auto-restart, monitoring, and logging. Not a Jupyter notebook — real infrastructure.
API layer
A clean REST API so your existing applications can call the model. Drop-in compatible with OpenAI/Anthropic APIs.
Security hardening
Network isolation, authentication, rate limiting, and audit logging. Meets compliance requirements for regulated industries.
Team training & runbooks
We train your IT team to manage, update, and troubleshoot the deployment. Full documentation, runbooks, and escalation paths.
Why on-premises AI?
Data sovereignty
Your data never leaves your network. Critical for healthcare, legal, finance, government, and defense.
Predictable costs
One-time setup + hardware. No per-token pricing that scales with usage. Heavy users save 60–80% annually vs. cloud APIs.
No vendor lock-in
Open-source models mean you’re never dependent on a single provider’s pricing decisions or policy changes.
Works offline
Your AI runs even when the internet goes down. Essential for manufacturing floors, remote sites, and air-gapped environments.
Built for industries that can't compromise on data
On-prem AI is the right choice when your data is too sensitive, too regulated, or too valuable to send to a third party.
Manufacturing
- Internal knowledge base for SOPs, safety data sheets, and formulations
- Quality control assistants that reference specs and tolerances
- Shift-handoff reports generated from floor data
Legal & compliance
- Confidential document search across case files and contracts
- AI-assisted due diligence on sensitive transactions
- Regulatory lookup that never sends data to a third party
Healthcare
- Clinical decision support from internal guidelines
- Patient record summarization that stays on-network
- HIPAA-compliant AI without cloud data exposure
Finance & government
- Internal policy Q&A for compliance teams
- Fraud pattern analysis on proprietary data
- Classified or sensitive document processing
How we deploy
Scoping call
We learn about your infrastructure, data, use case, and compliance requirements. 30 minutes, no commitment.
Architecture & proposal
You get a fixed-price proposal within 24 hours: hardware recommendations, model selection, deployment plan, and timeline.
Deploy & validate
We set up the infrastructure, deploy the model, connect it to your data, and run validation tests on your environment.
Handoff & support
Your team gets trained, documentation is delivered, and we provide 30 days of post-launch support to make sure everything runs smooth.
Typical investment
On-prem AI deployments typically range from $15K–$40K depending on hardware requirements, model complexity, and integration scope. This is a one-time cost — no recurring API fees, no per-query charges.
Every project starts with a free scoping call. You get a fixed-price proposal within 24 hours — no surprises, no scope creep.