Cloud
Useful when you need managed infrastructure, variable capacity, or models available through a hosted API.
Provider charges and terms apply. Review where data is processed, access controls, retention, and dependencies.
From a workflow to a working system.
Start with a decision, a build, or a deployment. Strategy, software, and infrastructure are connected — but you do not need to buy all three to have a useful conversation.
Understand
Find out whether AI is the right tool, which approach fits, and what evidence you need before committing a budget.
Good fit
A manual workflow, an uncertain AI proposal, or a team deciding whether to build, buy, or leave a process alone.
What you bring
The current process, representative examples, the people doing the work, and the constraints that cannot change.
Decisions & deliverables
A prioritized roadmap, build-versus-buy options, capability gaps, and a plan for evaluating the most useful next step.
What success means
A decision grounded in a specific workflow, its risks, and a measurable outcome — including a no-build recommendation when appropriate.
Build
Turn a defined workflow into a system that fits the software and people around it. Model output is an input to evaluate, not an answer to trust blindly.
Good fit
Document extraction, retrieval over internal knowledge, or a repeatable task that needs to connect to existing systems.
What you bring
Representative data, integration access, domain expertise, and examples of acceptable and unacceptable outputs.
Scope can include
Extraction and retrieval pipelines, tool-using agents, integrations, evaluation harnesses, and human-review boundaries.
How it is evaluated
Against agreed examples, failure cases, and workflow measures. Accuracy, review effort, latency, and cost need separate checks.
Deploy
Put the system in your cloud or on hardware you control. Specify the workload, data boundary, and operating responsibilities before choosing infrastructure.
Good fit
A workload with data-location requirements, sustained inference demand, or a need to operate without a public model API.
What you bring
Expected concurrency, model and context requirements, data restrictions, and the environment the system must run in.
Scope can include
Hardware specification, local model serving, integration, installation, operating documentation, and team handover.
Agree before deployment
Who handles updates, backups, incidents, hardware warranties, and ongoing support. These responsibilities are part of the scope, not implied by ownership.
Cloud, on-premises, or disconnected?
The right boundary depends on the data and the work. Compare total operating costs and responsibilities, not just the model bill.
Scope the work before estimating it.
Documents, integrations, review requirements, and deployment constraints determine the effort. Use the first conversation to identify the outcome, the information needed to assess it, and the right next step.
- Deliverables and what is out of scope
- Milestones, cost, and acceptance criteria
- Access to representative data and systems
- Licenses, handover, and ongoing responsibilities
Questions worth settling early.
Do we have to buy an appliance?
No. The deployment can be in your cloud or on your premises. A hosted service, a conventional automation, or no new system may be the better choice; the workflow comes first.
What does “AI you own” mean?
Control of the deployment and a clear handover of the project work. Ownership and usage rights belong in the agreement: third-party software and model weights remain subject to their respective licenses.
Does private inference mean no data ever leaves?
Not automatically. Inference, document storage, logs, backups, integrations, and support access are separate boundaries. Each needs an explicit design; the website enquiry form itself uses external hosting and email providers.
How much does a project cost, and how long does it take?
That depends on the workflow, data readiness, integrations, evaluation requirements, and infrastructure. Describe those constraints so the scope, milestones, and estimate can be discussed rather than guessed.
What happens after handover?
Agree who will run the system, how updates and failures will be handled, and whether ongoing support is needed. Handover should make those responsibilities clear; it is not a promise of an unspecified support service.