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Both, and usually together. Most engagements combine cloud infrastructure, deployment pipelines and at least one model or AI feature — we specialise in the point where software delivery and AI/ML delivery meet, not purely in one or the other.

An initial assessment is a fixed fee scoped to the size of the problem. After that you get a costed plan with a range rather than a single optimistic number, and a written change process if scope moves. Longer engagements are usually priced per sprint so you can stop at any milestone.

Yes, entirely and from day one. We build in your cloud account, your repositories and your model registry wherever possible, and all intellectual property transfers to you under the contract. There is no lock-in to us as a supplier.

Frequently. We can supply a complete delivery team, embed cloud/ML specialists into your existing squads, or own a defined workstream — such as the MLOps pipeline — while your team handles the rest.

Most clients move onto a support agreement covering monitoring, incident response and an agreed allocation of time each month for retraining or improvements. If you would rather run it yourselves, we do a structured handover with documentation and pairing sessions.