AI consulting and architecture
In short
AI consulting connects a business question with the practical requirements of using AI. I advise Taxara on technical and AI opportunities in UK accounting and fintech, and artists at The Gallery 21 on embracing AI. My software background helps connect those conversations to product scope, data needs and delivery decisions.
Founders without a technical co-founder, CTOs who want a second opinion on a big decision, and leadership teams working out where AI genuinely fits.
- A clear recommendation on where AI will and won't help, grounded in your real workflows.
- Architecture for a new product, or a review of an existing one with prioritised fixes.
- Buy, build, or integrate decisions for each part of the stack, with the exit cost of each.
- A delivery plan sized to your team and budget.
- Ongoing advisory support while your team builds.
- 1
Understand the business goal and the constraints — team, budget, data, deadlines.
- 2
Review what exists: code, architecture, vendors, and how work actually gets done.
- 3
Recommend a small number of decisions, each with its trade-offs written down.
- 4
Stay involved through delivery as much or as little as you need.
AI consulting and architecture: common questions
- Do you only advise, or do you also build?
- Both. Some teams want a plan they execute themselves; others want the Afiniti Global team to build it. The advice is the same either way.
- Where should a business start with AI?
- With a specific, measurable task that is costing time today — not with a technology. The best first projects are narrow, high-volume, and easy to check.
- Can you review an architecture our team has already designed?
- Yes. A review looks at the decisions that are hardest to change later — data model, vendor boundaries, authentication, observability, deployment — and flags the ones worth revisiting now.
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