Private & Self-Hosted AI

AI for data that can't leave your control.

Some data can't go to a hosted AI service, whatever the contract says. For that work, we deploy open-weight models on your own servers or a private environment you control.

Who it's for

Organizations whose contracts, regulators or own policies rule out sending certain data to a hosted model.

  • Contractors and firms doing government or federal work with data-handling restrictions
  • Financial and insurance firms with client data they won't send outside their environment
  • Life science teams with sensitive research or patient-related data
  • Any company whose legal team has said "not that data, not to an outside service"

What you get

  • Model selection

    We test open-weight models against your actual tasks and recommend one based on accuracy, speed and the hardware it needs. No guessing from benchmarks alone.

  • Infrastructure plan

    Where it runs: your servers, your private cloud account or a dedicated environment. Includes hardware or instance sizing and expected running costs.

  • Deployment

    The model, the serving layer and the connections to your internal documents and systems, all inside your boundary.

  • Access controls and logging

    User authentication, role-based access and logs of what was asked and answered, stored where you decide.

  • Honest trade-off review

    Open-weight models trail the leading hosted models on some tasks. We show you where that gap matters for your work and where it doesn't.

  • Hybrid option

    Where it makes sense, we route sensitive work to the private model and everything else to an enterprise hosted plan, with clear rules about which is which.

How it works

  1. Step 1: Classify the data

    We work with your security and compliance leads to decide which data must stay private and which tasks involve it.

  2. Step 2: Test models

    We run candidate open-weight models on representative tasks and compare results with you.

  3. Step 3: Deploy inside your boundary

    We stand up the model and its connections on your infrastructure or private environment, with access controls in place from day one.

  4. Step 4: Operate and update

    We monitor performance, apply updates and evaluate newer models as they're released, usually under a Managed AI Services retainer.

Frequently asked questions

Does self-hosting make us compliant?

No deployment makes you compliant on its own. Self-hosting keeps data inside your environment, which is often a key requirement. Your compliance program, policies and auditors still decide whether a use is acceptable. We don't claim HIPAA, GxP or FedRAMP certification.

Will a self-hosted model be as good as the big hosted ones?

For some tasks, close enough. For others, no. That's why we test on your actual work before you commit, and why a hybrid setup is often the right answer.

What does it cost to run?

It depends on the model size, usage and where it runs. The infrastructure plan gives you sizing and expected running costs before you buy hardware or reserve capacity.

Have data that can't leave the building?

Book a call. Tell us what the data is and what the restrictions are. We'll tell you what a private deployment would look like.

Book a discovery call