Private AI & deployment
Plan and implement AI workloads with data location, access, model lifecycle and infrastructure constraints in view. Explore customer-cloud, on-premises and constrained-environment deployment as engineering choices, with their dependencies made explicit.
Discuss your projectEnterprise technology leaders, infrastructure teams and organisations with controlled environments
Considered together.
Built around your work.
An AI workflow that works in a hosted demonstration may not fit your network, hardware, procurement or information policies. Model access, artifact movement, observability and operational support all need a plan. We help assess the complete environment before committing to a deployment approach.
Shape a workstream around the capabilities you need. The proposal defines which parts are included and how they will be evaluated.
Review where information can be processed, which external services are permitted and who operates the resulting system. Map compute, storage, networking and identity requirements.
The assessment distinguishes the desired deployment model from verified feasibility. On-premises and disconnected environments introduce specific packaging, update and support requirements; they are not labels applied to an unchanged cloud product.
Evaluate models and inference approaches against the task and available resources. Consider model size, supported runtimes, quality, latency and the effort required to operate the workload.
Where relevant, distillation can be evaluated through Bodhi. A smaller model is a candidate to test, not a guarantee of acceptable quality or lower total cost. Data and model-use permissions remain part of the scope.
Prepare the agreed application and model artifacts for the target environment. Define configuration, secrets handling, installation, versioning and the interfaces to surrounding systems.
Delivery can include deployment automation and controlled artifact transfer. The target hardware, image/runtime compatibility, network access and update mechanism must be validated in the actual environment.
Define how the owning team observes the service, changes configuration and handles incidents. Include model updates and application releases in the operating model.
Monitoring, backup expectations, rollback and support responsibilities are agreed explicitly. Availability commitments, managed operations and support hours are contractual scope, not assumptions attached to the word enterprise.
Concrete outputs to agree at the start of an engagement. The final scope depends on your systems, access and priorities.
Inside an engagement
Illustrative engagement: a team wants to use approved internal documents without assuming that all content can leave its network.
A deployment decision grounded in the actual workload and environment, with the quality and operating trade-offs visible.
Start with enough detail to make a good decision. Expand the work when the first scope has earned it.
Review the problem, existing systems and intended users. Identify the first complete workflow, its dependencies and the evidence that would demonstrate a useful result.
Agree responsibilities and review points. Develop the experience and technical implementation together, with working increments that can be inspected against the brief.
Review the result in the agreed environment. Document configuration, remaining limits and operating ownership. Ongoing support or further development is scoped explicitly.
Scope, responsibilities and commercial terms are agreed with your team.
That depends on the workload, model, licence and surrounding systems. We assess all dependencies before proposing a disconnected architecture and validate the chosen scope in the intended environment.
No. Deployment location is one technical consideration. Your organisation’s legal, security and compliance owners must assess the applicable obligations and the complete implementation.
It may, but the decision needs evidence. Quality, hardware utilisation, engineering effort, support and update costs all affect the comparison. We evaluate the task and deployment together.
Your next chapter
Bring us the work that matters.
We’ll find the right place to begin.
