AI Integration
AI applied where it helps, with the data handling settled first.
The problem
There is pressure to adopt AI and no agreement on what data may leave the organization.
What we do
We start with the use case and the data-handling constraints, because those decide what is possible. Where AI genuinely fits we build it with a human review step on anything consequential, and we say plainly when a simpler approach would work better.
Who this is for
Organizations with a specific problem in mind, rather than a mandate to use AI.
What you receive
- Use-case assessment with a recommendation
- Data handling and retention decisions, documented
- Working integration where it is justified
- Review and oversight process
How it works
Consultation
The problem and the constraints.
Assessment
Feasibility and data handling.
Proposal
What to build, or why not to.
Implementation
Build, evaluate, review.
Delivery
Handover and oversight process.
What we need from you
- A specific problem to solve
- A decision on what data may leave your control
These become your onboarding checklist — generated from the services you choose, so you are not asked for anything this work does not need.
Questions
Will you tell us if AI is the wrong tool?
Yes, and often. A great many problems presented as AI problems are reporting problems or process problems, and solving them that way is cheaper and more reliable.