Opportunity assessment
Choose a problem worth investing in.
Review workflows, priorities, data, and existing system conditions.
Possible deliverables
Opportunities / Pilot scope / Acceptance criteria
02 / Working together
From a business problem
to a measurable change.
Assessment, pilots, integration, and adoption. Let evidence clarify the scope, with concrete deliverables at each stage.
Pilots & integration
Validate the approach with a focused pilot.
Choose an approach around real tasks, test samples, and connect the required systems.
Possible deliverables
Working pilot / Evaluation / Handover
Improvement & adoption
Make it part of everyday work.
Address quality, cost, and workflow issues, with guidance, training, and maintenance arrangements.
Possible deliverables
Improvement plan / Guidance / Reviews
THE PROCESS
Find agreement. Then build on evidence.
01
Define the problem
Understand users, workflows, data, and current performance. Agree on goals, scope, and acceptance criteria.
02
Run a focused pilot
Test quality, total task time, cost, and human intervention on representative work before deciding to deploy.
03
Deploy and review
Connect the workflow, clarify handover and maintenance, and use performance to decide what comes next.
FAQ
Before we get started
Can we talk without a clear AI brief?
Yes. Start with a business problem, repetitive task, or bottleneck. We can assess whether AI is relevant and whether further evaluation makes sense.
Do you only work in industries you already know?
My direction is driven by business needs. In a new domain, I learn the context, research options, and test a focused approach. Delivery commitments follow validation and any necessary specialist collaboration.
Does accountability mean a guaranteed return?
Targets depend on your baseline, samples, and business conditions. Responsibility means clear goals, acceptance criteria, delivery, and review. It is not a fixed financial promise made before understanding the work.
How are cost, timing, and maintenance agreed?
They depend on scope, systems, validation work, and responsibilities. A concrete assessment informs the schedule, quote, maintenance ownership, and change handling.
What about data and AI errors?
We agree on data access and permitted use before selecting a solution. Quality standards, permissions, human review, and exception handling belong in the design. Important actions need appropriate confirmation.
Start with one problem
What would you
like AI to change?
Tell me about your business, the current process, and what you want to improve. We can assess whether the next step is worth taking.
Discuss your AI project