Development packages · Privately hosted models

Private / Local AI Engineering

Build software with AI development agents that run on privately hosted models, inside infrastructure you control or an isolated environment we agree with you. The same engineering, design, QA and release standards as every engagement.

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For controlled environments

Best fit when

Software delivery with suitable privately hosted models, inside a processing environment we agree with you. It's an engineering engagement, not GPU rental: we select and evaluate models, set up development agents and their permissions, and deliver with the same expert design, QA and release control.

  • Your policies don't allow source code or project context to be processed by external AI services.
  • You work with sensitive data, regulated workflows or valuable intellectual property.
  • You want a defined processing boundary your security team can review.
  • You'd like the option to run and improve the setup yourself later.

What the engagement includes

  • Model selection and evaluation

    We shortlist suitable open-weight coding models and evaluate them on tasks from your own codebase before committing to one.

  • Your infrastructure or an isolated one

    Models run on infrastructure you control or in an isolated environment we agree with you, with the boundary documented.

  • Development agents and permissions

    Agent tooling gets least-privilege access to repositories, environments and tools, and its changes go through review.

  • Code, prompts, research and data

    We agree how source code, prompts, research, test data, logs and integrations are stored, retained and accessed.

  • Expert engineering, design, QA and releases

    Engineers own architecture and reviews, designers own the experience, QA validates behavior and releases stay controlled.

  • Optional ongoing management

    We can keep operating the model environment after delivery: updates, monitoring, capacity and access reviews.

How it works

  1. 01

    Agree the boundary

    Map what must stay private (code, data, research, logs and outbound connections) and choose your infrastructure or an isolated environment.

  2. 02

    Evaluate and set up

    Test candidate models on your own tasks, size hardware to the workload and configure agents, access and logging.

  3. 03

    Build with expert control

    Engineers coordinate the agents and review their changes, with design, QA and DevOps in the same workflow.

  4. 04

    Release and operate

    Ship through controlled releases, then hand over the setup with documentation or let us manage it under a support plan.

Good to know

  • This package covers the AI tools used while we build. Your finished product can be hosted wherever its own requirements decide, including the cloud.
  • Hardware, hosting and model management are scoped and priced per engagement; nothing is a fixed bundle.
  • Deliverables depend on the engagement: a standalone UX review doesn't include running a model environment.

Also see:Claude Code / OpenAI Codex EngineeringCompare the packages in detail

FAQ

Private / Local AI Engineering: questions

Is this just renting a GPU?

No. Hardware is one input. The engagement covers model selection and evaluation, agent setup and permissions, how code and data are handled, and the engineering, design, QA and release work itself.

Will private models perform as well as leading cloud models?

Not necessarily; it depends on the task. We evaluate candidate models on work from your own codebase, explain the trade-offs and plan reviews and tests around them.

Does private development mean our product must run offline?

No. The package is about where AI tools process code and context while we build. Your product can run in the cloud, on your servers or offline, as its own requirements decide.

Does this make our project automatically secure or compliant?

No setup can promise that on its own. We define the processing boundary, access controls and logging with you and document them, so your security and compliance teams can review them.

Who runs the model environment after launch?

Your choice. We can hand it over with documentation and training, or manage it for you under an agreed support plan.

Planning a private AI setup?

Tell us what must stay inside your boundary and what you want to build. We'll propose an environment and a delivery plan.

Start a ProjectDiscuss Private / Local AI