Approach

Good AI work is less about the model, more about how the work is controlled.

Here's how an engagement runs, so you know what to expect before you commit a naira.

01

Discover

We start small. I look at the real problem, the constraints and your actual data before proposing a build – and you get a clear read on whether AI is even the right tool.

02

Scope

A written plan with explicit deliverables, assumptions, milestones and acceptance criteria. No open-ended "I'll work on it".

03

Build in the open

You see progress at each milestone, not just at the end. Drafts and demos go out as soon as they're useful, so you can redirect early.

04

Test & accept

Every deliverable is checked against the criteria we agreed. For AI systems that means evaluation against known cases – not "looks good to me".

05

Hand over & support

Documentation, a runbook and an agreed arrangement for maintenance and what happens after launch, so you're never stuck.

Delivery confidence

You should always know what's being built, why, and how we'll know it works.

A clear plan first

Scope, assumptions and milestones agreed before any building begins.

Measurable acceptance

Criteria set up front, with evals where it's an AI system.

Proactive updates

Progress and blockers raised early, not discovered at the deadline.

A real handover

Documentation, access and operational guidance that reduce dependence on me.
Start a project

Know exactly what you're committing to.

Most engagements start with a short, low-risk assessment. Tell me the problem in two lines.