Find the right problem.
Map the workflow, the time it takes and the constraints. Decide whether AI, simpler automation or no change is the right answer.
You get: a scoped opportunity and a clear next step.
A short initial conversation establishes fit. Paid discovery, implementation and ongoing support are separate decisions, with a written scope for each.
Map the workflow, the time it takes and the constraints. Decide whether AI, simpler automation or no change is the right answer.
You get: a scoped opportunity and a clear next step.
Implement a bounded pilot using agreed data. Test it against real examples, with a person in control of important decisions.
You get: a working pilot and acceptance evidence.
Document the workflow, train the people using it and agree who owns support, changes and ongoing costs.
You get: a practical handover, not a black box.
We discuss the process with the person doing the work, identify its cost and constraints, and agree a baseline.
If the likely value does not justify implementation, that is a useful finding. A build is not the automatic outcome.
We implement one agreed use case, using sample or appropriately authorised data. Your subject-matter owner reviews the outputs and exceptions.
Third-party model, hosting and software charges are identified separately. A pilot is not an automatic production rollout.
Where the pilot passes its acceptance criteria, we agree production scope and support responsibilities.
Project terms specify intellectual property, source access and third-party licensing. No implied 24/7 managed service.
No platform pitch required. Just a conversation about the work you want to improve.